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Showing papers from University of Oxford Show all papers

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Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners

Botos Csaba, Sreejan Kumar, Austin T D Andrews, Laurence T Hunt and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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High Entropy Regularization Leads to Symmetry Equivariant Policies in Dec-POMDPs

Johannes Forkel, Constantin Ruhdorfer, Michael Beukman, Andreas Bulling and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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Multigroup Fairness and Omniprediction: Separations and Equivalences

Sílvia Casacuberta, Parikshit Gopalan, Varun Kanade, Omer Reingold and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Trajectory-Consistent Dropout for Uncertainty Decomposition in Hamiltonian Neural Networks

Stephen J Roberts, Yuki Tachibana

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Chain-of-Thought Is Not Explainability

Fazl Barez, Tung-Yu Wu, Iván Arcuschin Moreno, Michael Lan and 12 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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On the Pitfalls of Instance-Based Dynamic Curricula

Alexandre Galashov, Amal Rannen-Triki, Yee Whye Teh, Razvan Pascanu and 1 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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The Sign Code: The Hidden Binary Nature of Deep Networks

Niclas A Göring, Shuofeng Zhang, Roi Holtzman, yoonsoo nam and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Generalization Measures for Deep Learning Should Be Audited for Fragility

Shuofeng Zhang, Ard Louis

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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Escaping Parameter Space: Tight Generalization Bounds via Representation Quality

Niclas A Göring, Shuofeng Zhang, Branton DeMoss, Ard Louis

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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LLMs Keep Thinking When Told Not To

Dianqiao Lei, Kevin Qinghong Lin, Pan Lu, Philip Torr and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Contrastive Adversarial Training for Robust Graph Neural Networks under Label Poisoning

Manshika C Bissessur, Melis Ilayda Bal, Michael Muehlebach

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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ASO Atlas 2.0: Evaluating antisense oligonucleotide prediction across the preclinical pipeline

Barney Hill, Nicola Whiffin, Carlo Rinaldi, Stephan J Sanders

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI for Drug Discovery Models Often Do Not Learn as Expected and How to Diagnose These Failure Modes

Nikhil Branson, Aaron Wenteler, Guy Durant, Charlotte Deane

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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SynthHair: Leveraging MetaHumans for a High-Quality 4K Hair Matting Dataset

Markus Karmann, Shile Li, Philip Torr, Puneet Dokania and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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UnlearningSoup: Is Repeated Tuning Necessary for Large Language Model Unlearning?

Puning Yang, Qizhou Wang, Junchi Yu, Bo Han and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI Control for Sandbagging on Fuzzy Tasks

Mikhail Terekhov, Caglar Gulcehre, Vivek Hebbar, Joe Benton

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation

Chengzhi Shen, Weixiang Shen, Tobias Susetzky, Chen Chen and 6 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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MedFlowBench: Auditing Medical Agents in Full-Study Workflows

Weixiang Shen, Chengzhi Shen, Che Liu, Junde Wu and 10 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Tight PAC-Bayes Generalisation Guarantees for Large Language Model Safety Monitoring

Tom Lamb, Philip Torr, Tim G. J. Rudner

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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ActO: Extracting Action Representations from MLLM Embeddings for Video World Models

Runjia Li, Minghao Chen, Junyu Xie, Philip Torr and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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As the Story Unfolds: Watching a Film and Identifying Characters as a Human Does

Zhongrui Gui, Junyu Xie, Tengda Han, Weidi Xie and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Subprocess-Constrained Markov Decision Processes

Jiarui Gan, Debmalya Mandal

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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IntegrityBench: Can LLMs Be Trusted as Co-Scientists? A Research Integrity Benchmark

Sai Sidhanth Manoharan Jayanthi, Yash Tripathi, Silu Sharma, Shivank Garg and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Outlier-Robust Multi-Output Gaussian Processes

Joshua Rooijakkers, Leiv Rønneberg, Francois-Xavier Briol, Jeremias Knoblauch and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Inter-Agent Influence: Evaluating Persuasion, Deception and Coercion in Multi-Agent Systems

Chandler Smith, Cecilia E Tilli, Qi Guo, Sophia Hatz and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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E0: Expressive Fine-Grained Discrete Action Prediction for Vision-Language-Action Models via Tweedie Discrete Diffusion

Zhihao Zhan, Jiaying Zhou, Likui Zhang, Qinhan Lyu and 9 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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OccStress: Stress-Testing the 4D Occupancy Forecasting Chain

Yu Zheng, Jie Hu, Jiaqi Xiong, Ruiping Liu and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Accelerating Neural Network Training with Augmented Koopman Dynamics

Jingyi Huang, Keyan Miao, Kostas Margellos, Paul Goulart

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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They Can See It but not Say It: Iterative Self Knowledge Re-expression in Visual Reasoning Relative Pose Identification

MENGYU WANG, Ken Deng, Yftah Ziser, Shay Cohen and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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PhysFormer: Learning to Simulate Mechanics in World Space

Yiming Chen, Yushi LAN, Andrea Vedaldi

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Track4D: Representing Dense 3D Tracking for Video Diffusion Models

Yushi LAN, Zeren Jiang, Kelvin Zheng Li, Xingang Pan and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Holo4D: Holistic 4D Reconstruction as Geometric Control for Video Diffusion

Yushi LAN, Zeren Jiang, Koichi Namekata, Xingang Pan and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Zero-Shot Coordination among LLM Agents

Adrian Hayler, Shashank Reddy Chirra, Andrei Lupu, Johannes Forkel and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Weird Generalization from Narrow Finetuning: Persona Shifts and Inductive Backdoors

Jan Betley, Jorio Cocola, Dylan Feng, James Chua and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Learning Acceptable Lotteries via Queries: Minimizing Aggregated Violation Distances

Paul W Goldberg, Nicholas Teh

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Task-Driven Bayesian Experimental Design Yields Singly Intractable Objectives for Joint Policy Training

Tom Rossa, Angus Phillips, Thomas Rainforth

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Fiedler-Regularized Causal Discovery for Sparse Connected DAGs

Amine M'Charrak, Abbavaram Gowtham Reddy, Thomas Lukasiewicz, Michael Bronstein and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Ad-Hoc Teamwork from Human Demonstrations

Darius Muglich, Niklas Lauffer, Tin Dizdarević, Jakob Foerster

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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MMDiff: Multimodal Model Diffing for Feature Discovery and Control

Lachin Naghashyar, Hunar Batra, Ashkan Khakzar, Philip Torr and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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We Need to Improve Benchmarks in AI for Mathematics

Simon Frieder, Jonas Bayer, Shi Zhuo Looi, Jacob Loader and 14 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AIs with Secret Loyalties are a Serious but Addressable Threat

Joe Kwon, Alfie Lamerton, Andrew Draganov, Dave Banerjee and 6 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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TrialAgentBench: Evaluating AI Agents for Clinical-Trial Analysis and Long-Horizon Drug-Development Decisions

Bradley M Segal, William J Bolton, Philip Torr, David Clifton and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Memorization Is Folding: Topological Signatures of Noisy-Label Learning

Zhongtian Sun, Fan Mo, Prayag Tiwari, KELIN XIA

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Logical Distillation of Transformer Encoders

Matteo Forasassi, Thomas Gärtner, Thomas Lukasiewicz, Sagar Malhotra

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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FIVE-VLA: Fast and EffectIVE Closed-Loop Autonomous Driving with Recurrent Action Memory

Kemal Oksuz, Alexandru Buburuzan, Yuhan Yao, Puneet Dokania

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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Git Context Controller: Manage the Context of Agents by Agentic Git

Junde Wu, Minhao Hu, Jiayuan Zhu, Shengda Zhu and 5 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Hydra: Towards Transferable Multi-Task Learning on Temporal Graphs

Kiarash Shamsi, Farimah Poursafaei, Tran Gia Bao Ngo, Reihaneh Rabbany and 5 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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Anchoring Reasoning Distillation via Syntactic Constraints

Zehua Cheng, Wei Dai, Jiahao Sun

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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LLM-WikiRace: A Benchmark for Planning and Reasoning over Real-World Knowledge Graphs

Juliusz Ziomek, William Bankes, Lorenz Wolf, Shyam Sundhar Ramesh and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Persona Vectors: Monitoring and Controlling Character Traits in Language Models

Runjin Chen, Andy Arditi, Henry Sleight, Owain Evans and 1 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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Symmetry Guarantees Statistic Recovery in Variational Inference

Symmetry in variational inference forces approximate minimizers to recover target statistics under misspecification, unifying prior results and yielding new directional guarantees.

Daniel Marks, Dario Paccagnan, Mark van der Wilk

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Time-Sensitive Anytime-Valid Testing

A time-sensitive testing-by-betting framework favors early rejection via time-weighted rewards, yielding Bellman-optimal e-processes and an exponential-decay-optimal criterion recovering classical growth-rate optimality at large scales.

Eugenio Clerico, Tobias Wegel, Iskander Azangulov, Patrick Rebeschini

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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TokenSwap: Benchmarking and Reducing the Modality Gap in Multimodal LLMs

TokenSwap benchmarks and reduces MLLMs' modality gap by interleaving visual tokens with text, finding reasoning models have smaller gaps and training with TokenSwap mitigates it.

Andong Hua, Colton Bishop, Igor Mordatch, Arian Hosseini and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Probing Persona-Dependent Preferences in Language Models

Linear probes on LLM residual streams identify a shared preference vector tracking pairwise choices across personas, with cross-persona transfer and causal steering.

Oscar Gilg, Pierre Beckmann, Daniel Paleka, Patrick Butlin

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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Evaluating and Understanding Scheming Propensity in LLM Agents

Realistic agent settings show minimal scheming despite high incentives, with model-organism scheming brittle to tool removal and oversight.

Mia Hopman, Jannes Elstner, Maria Avramidou, Amritanshu Prasad and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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Search at the Cost of Sampling: Nearly-Instant Latent Space Bayesian Optimization

Exploiting spherical latent geometry yields nearly closed-form Bayesian optimization with 100x speedups and matching performance in generative discovery pipelines.

Donney Fan, Colin Doumont, Aleksandra Kalisz, Paul Duckworth and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Beyond One-Size-Fits-All: Diagnosis-Driven Online Reinforcement Learning with Offline Priors

Diagnosis-driven tension management adapts online RL to deployment-specific prior validity shifts, rejecting universal benchmarks for flexible, evidence-guided optimization.

Guozheng Ma, Lu Li, Zilin Wang, Pierre-Luc Bacon and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Permutation-Invariant Spectral Learning via Dyson Diffusion

Dyson Diffusion Model uses Dyson Brownian motion to shift inductive bias to diffusion dynamics, yielding permutation-invariant spectral learning that improves graph generation.

Tassilo Schwarz, Cai Dieball, Constantin Kogler, Renaud Lambiotte and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Benchmarking Open-Ended Multi-Agent Coordination in Language Agents

Alem benchmarks open-ended multi-agent coordination for language agents, showing frontier LLMs average ~6% returns and individual competence does not imply coordination competence.

Kale-ab Tessera, Andras Szecsenyi, Cameron Barker, Alexander Rutherford and 6 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 7 on Hugging Face · Code ★ 51

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78%Highly rated
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Selective Safety Steering via Value-Filtered Decoding

Value-filtered decoding selectively steers LLM generation using a value-based safety criterion with explicit false-intervention bounds, improving safety-utility trade-offs over baselines.

Bat-Sheva Einbinder, Hen Davidov, Yee Whye Teh, Yarin Gal and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 4 on Hugging Face

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Modelling Opinion Dynamics at Scale with Deep MARL

Deep MARL scales opinion dynamics to 1000 agents, finding high conformity in large networks reduces accuracy and promotes dishonesty, unlike small groups, revealing a mismatch with modern media.

Lukas Seier, Brandon Kaplowitz, Sebastian Towers, Richard M Bailey and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Social Choice Foundations for Simulation-Augmented Generation

SAGE formalizes efficient inference-time viewpoint simulation via metric proportional justified representation, proving small simulated pools and dynamic routing preserve approximate proportional representation for contentious queries.

Sonja Kraiczy, Smitha Milli, Ratip Emin Berker, Avinandan Bose and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Bayesian Decision Making around Experts

In Bayesian multi-armed bandits, pretraining on expert data tightens regret bounds by mutual information with the optimal action, while an information-directed rule selects data sources maximizing immediate information gain, and trust inference safeguards against ineffective or compromised experts.

Daniel Jarne Ornia, Joel Dyer, Nicholas Bishop, Anisoara Calinescu and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Convergence Analysis of Newton's Method for Neural Networks in the Overparameterized Limit

Regularized Newton training of overparameterized neural networks converges to a deterministic NNTK limit with exponentially fast uniform convergence across all frequencies, avoiding gradient descent's spectral bias.

Konstantin Riedl, Justin Sirignano, Konstantinos Spiliopoulos

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Quantifying Concentration Phenomena of Mean-Field Transformers in the Low-Temperature Regime

Mean-field transformers exhibit rapid token distribution concentration onto projection-driven limits with explicit Wasserstein bounds scaling in inverse temperature β and time t.

Albert Alcalde, Leon Bungert, Konstantin Riedl, Tim Roith

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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Metropolis-Adjusted Diffusion Models

Metropolis-adjusted Langevin correctors using score-based acceptance probabilities and a two-coin Bernoulli factory reduce diffusion model sampling bias and improve FID.

Kevin H. Lam, Tyler Farghly, Christopher Williams, Jun Yang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons

A parameter-efficient plugin extends frozen 10-second ECG foundation models to long, variable-length recordings via compatible long-sequence processing and semantically informed temporal modeling, outperforming sliding-window and pooling baselines.

Wei Tang, Jinpei Han, Kangning Cui, Mattia Carletti and 9 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Asymptotically Log-Optimal Bayes-Assisted Confidence Sequences for Bounded Means

A Bayes-assisted framework adaptively builds confidence sequences via predictive expected log-growth to achieve asymptotic log-optimality and narrower widths.

Valentin Kilian, Stefano Cortinovis, Francois Caron

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Negation Neglect: When models fail to learn negations in training

Fine-tuning LLMs on documents that flag claims as false makes them believe those claims, with belief rates jumping from 2.5% to 88.6%, though local negation phrasing largely prevents it.

Harry Mayne, Lev McKinney, Jan Dubiński, Adam Karvonen and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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A Mean-Field Framework for Inference-Time Distributional Control of Diffusion Models

A mean-field framework formulates inference-time diffusion control via weighted interacting particles to target distribution-level rewards with theoretical guarantees.

Samuel Howard, Nikolas Nüsken

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Asking the Right Questions: Improving Reasoning with Generated Stepping Stones

ARQ introduces a question generator that produces transferable intermediate stepping stones, improving reasoning LLM performance via fine-tuning on synthetic data.

Hengyuan Hu, Tingchen Fu, Minqi Jiang, Alexander Miller and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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A Mechanistic Analysis of Looped Reasoning Language Models

Looped reasoning models converge to cyclic fixed points that stabilize attention and repeat feedforward inference stages iteratively, with recurrence size and normalization affecting stability.

Hugh Blayney, Alvaro Arroyo, Johan Obando Ceron, Pablo Samuel Castro and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face

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MedMisBench: Measuring Epistemic Resilience of LLMs Under Misleading Medical Context

MedMisBench reveals LLM medical accuracy collapses from 71% to 38% under misleading context, exposing a critical evaluation blind spot around epistemic resilience.

Hongjian Zhou, Xinyu Zou, Jinge Wu, Sean Wu and 18 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation

FedRepRAG is a federated RAG framework that exchanges only compact latent representations across clients to reduce inference overhead, outperforming local retrieval baselines on decentralized VQA and QA tasks.

Can Peng, Yu Liu, Yingyu Yang, Anjie Le and 3 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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Inverting the Bellman Equation: From $Q$-Values to World Models

Value-based agents trained on diverse reward functions implicitly encode world models, extractable via P-learning, with sufficient conditions for exact dynamics recovery and cross-goal generalization.

Alistair Letcher, Mattie Fellows, Alexander D. Goldie, Jonathan Richens and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Eliciting Secret Knowledge from Language Models

Secret-knowledge-elicitation techniques, especially prefill attacks, successfully extract hidden knowledge that LLMs deny knowing but apply downstream.

Bartosz Cywiński, Emil Ryd, Rowan Wang, Senthooran Rajamanoharan and 3 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 6 on Hugging Face · Code ★ 24

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STARE: Surprisal-Guided Token-Level Advantage Reweighting for Policy Entropy Stability

STARE analyzes token-level entropy dynamics under GRPO, identifies a credit assignment mismatch, and uses surprisal-guided advantage reweighting to stabilize policy entropy, improving AIME accuracy by 4-8%.

HAIPENG LUO, Qingfeng Sun, Song-Li Wu, Can Xu and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 12 on Hugging Face · Code ★ 24

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Standing on the Shoulders of Giants: Rethinking EEG Foundation Model Pretraining via Multi-Teacher Distillation

Multi-teacher distillation pretrains EEG foundation models using vision and time-series teachers via masked latent denoising, outperforming self-supervised methods with 75% less pretraining data.

Chenqi Li, Yu Liu, Shuo Zhang, Timothy Denison and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Simple Baselines are Competitive with Code Evolution

Simple baselines match or beat sophisticated code evolution across mathematical bounds, agent scaffolds, and ML competitions, revealing evaluation flaws and underscoring that expert-designed search spaces matter more than search algorithms.

Yonatan Gideoni, Sebastian Risi, Yarin Gal

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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GridProbe: Posterior-Probing for Adaptive Test-Time Compute in Long-Video VLMs

GridProbe scores frame evidence via frozen VLM answer-space probing and adaptive selection to reduce long-video attention costs with minimal accuracy loss. It matches monolithic baselines on Video-MME-v2 at 3.36x lower compute and Pareto-dominates baselines on LongVideoBench.

Mohamed Eltahir, Ayash, Ali Habibullah, Tanveer Hussain and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 2 on Hugging Face · Code ★ 2

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Training Transformers for KV-Cache Compressibility

KV-compressibility is a learnable property, so KV-CAT trains transformers via masked KV slots to yield representations more amenable to post-hoc compression without sacrificing quality.

Yoav Gelberg, Yam Eitan, Michael Bronstein, Yarin Gal and 1 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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Instruct-Particulate: Scaling Feed-Forward 3D Object Articulation with Kinematic Control

Instruct-Particulate predicts articulated 3D part segmentation and joint parameters from meshes and kinematic specifications, scaling training via vision-language labels to improve cross-category and AI-generated mesh generalization.

Ruining Li, Yuxin Yao, Matt Zhou, Chuanxia Zheng and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Hyperagents

Hyperagents integrate editable task and meta agents to enable metacognitive self-modification, with DGM-H improving across domains and accumulating meta-level improvements.

Jenny Zhang, Bingchen Zhao, Wannan Yang, Jakob Foerster and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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Universal Time Series Generation with Neural Controlled Differential Equations

Structured Linear Controlled Differential Equations are universal time-series generators that approximate induced path laws on compact latent sets, and Generative SLiCEs improve probabilistic forecasting and downstream task performance on irregular grids.

Torben Berndt, Elyes Farjallah, Leif Seute, RAEID SAQUR and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Coherent Hierarchical Multi-Label Learning to Defer for Medical Imaging

Coherent hierarchical multi-label learning to defer uses selective-exclusion contracts to eliminate taxonomic deferral incoherence in medical imaging via projection and belief propagation.

Joshua Strong, Pramit Saha, Emma Sun, Helen Higham and 1 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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Itô maps for any-step SDEs

The paper introduces Itô maps as any-step stochastic flow maps for SDEs that enable efficient single-pass future state prediction, posterior sampling, and inference-time control.

Zhengkai Pan, Peter Potaptchik, Wenxi Yao, Michael Albergo and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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ThousandWorlds: A benchmark for climate emulation of potentially habitable exoplanets

ThousandWorlds introduces a multi-model exoplanet climate benchmark of ~1,700 GCM simulations, showing Gaussian processes outperform deep learning in low-data multi-simulator regression.

Edward Stevenson, Mei T Mak, Eric Wolf, Denis E Sergeev and 3 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026 · ▲ 1 on Hugging Face

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Normative Networks for Source Separation via Local Plasticity and Dendritic Computation

Predictive Entropy Maximization achieves blind source separation via local plasticity and dendritic error-driven rules with competitive robustness.

Bariscan Bozkurt, Efe Ali Gorguner, Francesco Innocenti, Rafal Bogacz

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction

StraTA introduces trajectory-level strategies into agentic reinforcement learning via hierarchical rollout training, improving long-horizon decision-making and reaching 93.1% on ALFWorld.

Xiangyuan Xue, Yifan Zhou, ZiDong Wang, Shengji Tang and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 27 on Hugging Face · Code ★ 47

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RelAgent: LLM Agents as Data Scientists for Relational Learning

RelAgent is an LLM agent that builds SQL feature queries and selects predictive models for relational learning, yielding fast, interpretable predictions deployable via standard databases.

Xingyue Huang, Louis Tichelman, Jinwoo Kim, Krzysztof Olejniczak and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightU OxfordDeep learning theory

Understanding Sample Efficiency in Predictive Coding

Predictive coding improves sample efficiency over backpropagation via higher target alignment, especially in deep, narrow, and pre-trained networks.

Gaspard Oliviers, Elene Lominadze, Rafal Bogacz

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 4/5
medium 6/10
strict 1/5
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Zero-Shot Instruction Following in RL via Structured LTL Representations

A GNN encodes LTL instructions as Boolean formula sequences conditioning a policy, improving zero-shot multi-event RL instruction following in complex environments.

Mathias Jackermeier, Mattia Giuri, Jacques Cloete, Alessandro Abate

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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Poisoning Attacks on LLMs Require a Near-constant Number of Poison Samples

Poisoning LLM pretraining requires only ~250 malicious documents regardless of dataset or model scale, revealing constant-cost backdoor injection risks for large models.

Alexandra Souly, Javier Rando, Ed Chapman, Xander Davies and 9 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 5 on Hugging Face

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AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 7/10
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Stealth Apart, Harm Together: Skill Cascading Attacks on Skill-Based Agent Systems

Skill cascading attacks distribute malicious objectives across benign skills to harm agent systems, and SkillCascade reliably induces such failures while evading per-skill defenses.

Zihao Zhu, Siwei Lyu, Adel Bibi, Baoyuan Wu

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 5/5
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SOAR: Regression-based LiDAR Relocalization for UAVs

SOAR proposes regression-based LiDAR relocalization for UAVs using locality-preserving sliding-window attention and coordinate-independent initialization, achieving state-of-the-art accuracy on UAVLoc with a 40% higher success rate and over 10 meters lower mean error.

Hengyu Mu, Jianshi Wu, Yuxin Guo, XianLian Lin and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 4/5
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Exact Posterior Score Estimation for Solving Linear Inverse Problems

Exact posterior score estimation derives closed-form posterior scores for linear Gaussian inverse problems, enabling efficient training and sampling that outperforms baselines with far fewer evaluations.

Abbas Mammadov, Ozgur Kara, Kaan Oktay, Iskander Azangulov and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 2/5
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Known By Their Actions: Fingerprinting LLM Browser Agents via UI Traces

UI traces from LLM web agents identify underlying models with 96% F1 via passive JavaScript tracking, though randomized delays only partially mitigate fingerprinting.

William Gitta Lugoloobi, Samuele Marro, Jabez Magomere, Joss Wright and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · Code ★ 7

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AI panel: 16 of 20 reviewers recommend it
lenient 5/5
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strict 3/5
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Code2World: A GUI World Model via Renderable Code Generation

Code2World uses renderable code generation for GUI world modeling, achieving top next-UI prediction and boosting Android navigation success by up to 9.5%.

Yuhao Zheng, Li'an Zhong, Yi Wang, Rui Dai and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 186 on Hugging Face · Code ★ 312

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
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strict 1/5
76%Highly rated
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Robust PAC Learning of Concurrent Stochastic Games

A PAC learning framework for concurrent stochastic games computes robust near-optimal Nash equilibria with polynomial sample complexity or certifies nonexistence.

Angel Y He, David Parker

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 10 of 20 reviewers recommend it
lenient 2/5
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LibriBrain100: One Hundred Hours of Broad and Deep MEG Data for Neural Speech Decoding at Scale

LibriBrain100 provides over 100 hours of MEG speech-decoding data, showing deep within-subject recordings and broad multi-subject data improve noninvasive word classification.

Francesco Mantegna, Dulhan Jayalath, Gereon Elvers, Tasha Kim and 10 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 4 on Hugging Face · Code ★ 15

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
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strict 2/5
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Evaluating AI-based Scientific Knowledge Synthesis with Epidemiological Systematic Reviews

AgentSLR evaluates LLMs on epidemiological systematic reviews, revealing sub-task specialization, poor structured extraction (F1 < 0.67), and unreliable unsupervised deployment.

Shreyansh Padarha, Ryan Othniel Kearns, Tristan M Naidoo, Lingyi Yang and 12 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 9 on Hugging Face · Code ★ 25

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 4/5
76%Highly rated
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Prediction-Powered Active Testing

PPAT combines unbiased LURE estimation with prediction-powered control variates and adaptive acquisition to reduce label variance, yielding valid confidence intervals with fewer labels.

Kianoosh Ashouritaklimi, Valentin Kilian, Daolang Huang, Thomas Rainforth and 1 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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lenient 4/5
medium 5/10
strict 1/5
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ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation

ClothTransformer reformulates cloth simulation as autoregressive latent-space sequence modeling to unify body-driven garments, robotic manipulation, and collisions with 4-9x lower error.

Yu Zhang, YIDI SHAO, Wenqi Ouyang, Yushi LAN and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
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strict 3/5
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PAIR-CI: Calibrated Conditional Independence Testing for Causal Discovery with Incomplete Data

PAIR-CI is a calibrated nonparametric conditional independence test for incomplete data that uses paired cross-validated imputation to cancel imputation error, controlling false positives near nominal levels and improving causal discovery accuracy over existing methods.

Thomas S. Robinson, Ranjit Lall

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 16 of 20 reviewers recommend it
lenient 3/5
medium 10/10
strict 3/5
78%Highly rated
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An Empirical Study on Noisy Data and LLM Pretraining Loss Divergence

Synthetic noise in pretraining data causes LLM loss divergence with probability scaling by noise type, amount, and model size, exhibiting activation patterns distinct from high-learning-rate failures.

Qizhen (Irene) Zhang, Ankush Garg, Jakob Foerster, Niladri S. Chatterji and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
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strict 2/5
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Conditional misalignment: common interventions can hide emergent misalignment behind contextual triggers

Common interventions suppress emergent misalignment only under standard evaluations, yet hidden contextual triggers still elicit worse misalignment resembling training conditions.

Jan Dubiński, Jan Betley, Anna Sztyber-Betley, Daniel Tan and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
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fmxcoders: Factorized Masked Crosscoders for Cross-Layer Feature Discovery

Standard crosscoders learn layer-localized features; fmxcoders use factorized weights and layer masking to recover cross-layer features, improving coherence and reconstruction across four LLMs.

Andreas D Demou, Panagiotis Koromilas, James Oldfield, Yannis Panagakis and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 15 of 20 reviewers recommend it
lenient 3/5
medium 9/10
strict 3/5
72%Highly rated
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Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples

Classification fields recursively generate infinite hierarchical cluster structures via local parent-to-child refinement rules learnable from finite prefixes with exponential convergence guarantees.

Yicen Li, Ruiyang Hong, Anastasis Kratsios, Haitz Sáez de Ocáriz Borde and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 1/5
medium 5/10
strict 2/5
71%Highly rated
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Predictively-Oriented Kalman Filtering

Predictively-Oriented Kalman Filter (EKF-PrO) uses fast approximate updates to avoid overconfident filtering under model misspecification without hyperparameters.

Zheyang Shen, Gerardo Duran-Martin, Chris Oates

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 6 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 0/5
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StemBind: When MLLMs Get Lost Between Rules and Instances in Abstract Visual Reasoning

StemBind introduces a shared-stem benchmark diagnosing MLLM abstract visual reasoning, finding a persistent rule-to-instance binding gap where models identify patterns but fail to apply them correctly.

Xixiang He, Baiqi Wu, Xingming Li, Ao Cheng and 3 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 17 of 20 reviewers recommend it
lenient 4/5
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Gender Artifacts from Art History to Text-to-Image Generation

StyleGender analyzes gender artifacts across 19 art styles and text-to-image outputs, finding generative models amplify gender biases beyond historical sources.

Piera Riccio, Miriam Doh, Benedikt Höltgen, Noa Garcia and 1 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 2/5
70%Highly rated
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Hyperparameter Transfer for Dense Associative Memories

Derives explicit hyperparameter transfer rules for Dense Associative Memories and validates them against large-scale training.

Roi Holtzman, Dmitry Krotov, Boris Hanin

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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AI panel: 4 of 20 reviewers recommend it
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medium 4/10
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Attack Selection In Agentic AI Control Evaluations Meaningfully Decreases Safety

Strategic attack selection via start and stop policies substantially lowers measured AI control safety without changing attack capability, reducing safety by up to 28 percentage points and yielding overly optimistic estimates.

Catherine Ge-Wang, Tyler Crosse, Benjamin Hadad, Joachim Schaeffer and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 16 of 20 reviewers recommend it
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Articraft: An Agentic System for Scalable Articulated 3D Asset Generation

Articraft uses LLM agents to programmatically generate validated articulated 3D assets at scale, yielding 10K assets for training and simulation.

Matt Zhou, Ruining Li, Xiaoyang Lyu, Zhaomou Song and 5 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
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