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Showing papers from University of Warwick Show all papers

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NeurIPS 2026U WarwickOffline RL

Distributionally-Robust Policy Learning from Observational Data

Debmalya Mandal

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

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medium 0/10
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67%Highly rated
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NeurIPS 2026HubSpot, Inc.Huazhong University of Science aNanyang TechnologicalWuhanU WarwickAdversarial robustness

Cross-Model Transfer Attacks against Large Vision-Language Models via Model Diversity Enrichment and Stochastic Parameter Sampling

Zhenze Yang, Xiaowen Cai, Junhao Dong, Guangke Chen and 7 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: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
45%Niche pick
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NeurIPS 2026U OxfordU WarwickDeep RL

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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NeurIPS 2026Imperial College LondonU WarwickMultimodal reasoning

Look Before You Reason: Implicit Visual Thinking for Efficient Multimodal Reasoning

Zerui Chen, Changrui Chen, Fei Ni, Jiankang Deng

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

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NeurIPS 2026U WarwickdatabricksAutoML & architecture search

MOBO-CAPS: Multi-objective Bayesian Optimization with Cardinality-Aware Pareto Selection

Hanyang Wang, Juergen Branke, Matthias Poloczek

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

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NeurIPS 2026Imperial College LondonKing's College London, UnivTianjinU WarwickRobot manipulation

PACE: Progress Actively-internalized Conditioning Execution for Long-horizon Manipulation

Fei Ni, Zhuo Chen, Xianze Yao, Zerui Chen 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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57%Worth a look
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NeurIPS 2026NortheasternU WarwickUnited States Military AcademyAdversarial robustness

When Uncertainty Is the Target: Adversarial Attacks on Uncertainty-Aware Predictors

A Q M Sazzad Sayyed, Michele Caprio, Nathaniel D Bastian, Francesco Restuccia

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

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lenient 1/5
medium 0/10
strict 0/5
71%Highly rated
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NeurIPS 2026U Illinois ChicagoU Illinois at ChicagoU WarwickGraph neural networks

GRAPHLCP: Structure-Aware Localized Conformal Prediction on Graphs

GRAPHLCP integrates graph topology and inter-node dependencies into localized conformal prediction via densification and PageRank-based structural proximity, improving conditional coverage efficiency on graphs.

Peyman Baghershahi, Fangxin Wang, Debmalya Mandal, Sourav Medya

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

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AI panel: 7 of 20 reviewers recommend it
lenient 3/5
medium 4/10
strict 0/5
74%Highly rated
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NeurIPS 2026Pennsylvania StateU WarwickAlignment & preference optimization

Inference Time Nash Alignment

Inference-time alignment via Nash equilibrium achieves lower-bound duality gaps and matches fine-tuned performance without parameter updates.

Hadi Hosseini, Debmalya Mandal, Duohan Zhang

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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AI panel: 9 of 20 reviewers recommend it
lenient 2/5
medium 6/10
strict 1/5
91%Must read
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NeurIPS 2026U WarwickSpotifyU TartuSpotify & University CollegeRecommender systems

Causal Representation Learning for Generalisable Recommendation

A causal disentanglement objective improves recommender out-of-distribution generalization by isolating invariant causal components, yielding substantial online engagement gains in Spotify A/B tests.

Yorgos Felekis, Michael O'Riordan, Oriol Corcoll Andreu, Ciarán Gilligan-Lee

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

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5
71%Highly rated
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NeurIPS 2026The University of WarwickQueen's University BelfastU WarwickMulti-agent RL

The Dynamics of Policy Gradient in Social Dilemmas with Partner Selection

Policy-gradient dynamics with partner selection are solved analytically, proving population variance is necessary for cooperation and deriving conditions for a stationary cooperative distribution.

Benedict Russell, Chin-wing Leung, Paolo Turrini

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

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AI panel: 7 of 20 reviewers recommend it
lenient 3/5
medium 3/10
strict 1/5
71%Highly rated
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NeurIPS 2026RIKEN AIPU WarwickU AmsterdamExplainable AI

Guided Data Generation for Understanding Model Behavior

A guided data generation framework generates input distributions to inspect trained model behaviors via specification functions.

Eren Mehmet KIRAL, Nursen Aydin, Ilker Birbil

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

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6/20 AI panelreviewers recommend it

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AI panel: 6 of 20 reviewers recommend it
lenient 4/5
medium 1/10
strict 1/5
80%Must read
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NeurIPS 2026MonashMiniMaxBeijing Geling Deep Eye InformatDEEP GLINTMicrosoft Research AsiaVision-language models

OneVision-Encoder: Codec-Aligned Sparsity as a Foundational Principle for Multimodal Intelligence

OneVision-Encoder applies codec-aligned sparsity to video, processing only high-entropy regions to outperform dense backbones with fewer tokens. It achieves 4.1% higher video accuracy than Qwen3-ViT across 16 benchmarks.

feilong tang, Xiang An, Yunyao Yan, Yin Xie and 14 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026 · ▲ 52 on Hugging Face · Code ★ 403

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12/20 AI panelreviewers recommend it

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AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 1/5
86%Must read
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NeurIPS 2026Isomorphic LabsSLAC / StanfordTechnical University of MunichU WarwickEfficient & distributed training

It Just Takes Two: Scaling Amortized Inference to Large Sets

A mean-pool DeepSet trained on pairs learns set encoders that generalize to arbitrary sizes, letting inference heads scale to thousands of observations with minimal compute.

Antoine Wehenkel, Michael Kagan, Lukas Heinrich, Chris Pollard

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

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 3/5