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arXivJilinLLM evaluation & benchmarks

More Choices, Fewer Decisions: Ordinal-Scale Bias in JEV-like Direct-Decision Models

Direct-decision JEV models show ordinal scale-utilization bias, compressing decisions to 26, 76% of gold support despite high accuracy, but BA-LoRA post-training improves utilization to 86%.

Tianxiang Gao, Jinzhe Li, Zhiyuan Li, Yi Chang and 1 more

Published Sep 30, 2026 · 0 citations · ▲ 60 on Hugging Face · Code ★ 3

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NeurIPS 2026JilinHarbin Institute of TechnologyHarbin Institute of Technology, TsinghuaHarbin Institute of Technology,SMachine unlearning

Differential Vector Erasure: Unified Training-Free Concept Erasure for Flow Matching Models

Zhiqi Zhang, Xinhao Zhong, Yi Sun, Shuoyang Sun 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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NeurIPS 2026JilinJilin University, ChinaGraph transformers

DualSAT: A Dual-Branch GNN-Transformer Framework for SAT Solving

Wenzhu Yang, Zhanshan Li, Jingyao Li

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

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NeurIPS 2026HarvardStanfordJilinByteDance Inc.Vision-language models

Render Structure Uncertainty for HTML Repair in MLLM-based UI-to-Code Generation

Haoran Ma, Jiechao Gao, Shisong Tang, bing han 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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67%Highly rated
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NeurIPS 2026Syneron BioJilinChangchun University of Science Communication University of ChinSyneron OpalMolecules & drug discovery

PepDDG: Peptide–Protein Binding ΔΔ𝐺 Prediction via Information Channel Decomposition

Ruochi Zhang, Yusi Fan, Qiong Zhou, Li Jiao and 9 more

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

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NeurIPS 2026Mohamed bin Zayed University of The University of SydneyHKBU / RIKENJilinHong Kong PolytechnicMaterials & chemistry

MaterialsPilot: An Execution-Feedback Framework for Generative Design of Complex Atomistic Architectures

Qiaolin Lu, Tongliang Liu, Qiang Qu, Bo Han 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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NeurIPS 2026The University of SydneyHarbin Institute of Technology SU Sydney, University of SydneyHKBU / RIKENMohamed bin Zayed University of Materials & chemistry

Symmetry-Guaranteed Prediction of High-Order Tensor Properties for Crystalline Materials via Irreducible Decomposition

Qiaolin Lu, Qiang Qu, Hao Jiang, Aoni Xu 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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NeurIPS 2026U Science and Technology of ChinStanfordJilinImage recognition

U-MOF: Uncertainty-Guided Parameter-Efficient Multi-Objective Fine-Tuning for Long-Tailed Recognition

Yuan Dong, Di Wu, Zhe Zhao, Liheng Yu 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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NeurIPS 2026U Science and Technology of ChinStanfordJilinImage recognition

BasicLT: Basic-Level Abstraction and Selective Differentiation for Long-Tailed Recognition

Yuan Dong, Di Wu, Zhe Zhao, Liheng Yu and 3 more

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

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NeurIPS 2026XiamenJilinChina Electric Power Research IChina Electric Power Research InU YorkDynamic graphs

WavCIL: Wavelet Coefficient-Domain Invariant Learning for Dynamic Graph OOD Generalization

Yantong Zhu, Weining Shi, Keyi Li, Xiaoyan Xie 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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NeurIPS 2026NanKaiNankaiShandong JianzhuJilinHarbin Institute of TechnologyVision-language models

Counterfactual Instruction Grounding for Vision-Language-Action Models

Shiyu Liu, Yu Zhou, Meng Liu, Xuanming Guo 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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NeurIPS 2026JilinQuantization

ASVQ: What Reparameterization Is Just Enough for Efficient Codebook Learning?

Wenfeng Zou

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

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NeurIPS 2026Hong Kong PolytechnicMonashInternational Digital Economy AcJilinGriffithLLM reasoning & chain of thought

MemPilot: Learning Transferable Latent Memory Mechanisms for LLM Reasoning

Changlong Shi, LINHAO LUO, Shigeng Chen, Guibin Zhang 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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NeurIPS 2026PekingJilinNew York Institute of TechnologyBeijing University of AeronauticCapital NormalVideo-language models

Behavior Pack Optimization for Video MLLM Post-Training

Zhaolu Kang, Shiyu Liu, Tailong Luo, Wei Zhang and 11 more

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

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NeurIPS 2026JilinOffline RL

Optimistic Q-value Adaptation for Offline-to-Online Reinforcement Learning

Hao Wu, Shunhao Zhang, Shuai Lü

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

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NeurIPS 2026JilinInner MongoliaMBZUAI/Jilin U.Test-time compute

Achieve Latency-Efficient Temporal-Coding Spiking LLMs via Discretization-Aware Conversion

Jinjie Fang, Tianxing Man, Xiao Du, Chengxun Jin and 3 more

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

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NeurIPS 2026JilinMBZUAI/Jilin U.Pruning & sparsity

Unifying Sparsity and Discreteness: One-Shot Pruning for Quantized LLMs via Discrete Optimization

Haozhen Zhang, Hanyuan Zheng, Teng Hou, Zhaogeng Liu and 2 more

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

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NeurIPS 2026JilinMBZUAI/Jilin U.Instruction tuning

Towards Identifying Dominant Low-Rank Subspaces in Zeroth-Order Fine-Tuning

Jinjie Fang, Chengxun Jin, Yi Chang, Bin Gu

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

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69%Highly rated
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NeurIPS 2026Institute of Automation, ChineseJilinTencent YouTu LabHangzhou DianziHuazhong University of Science aWatermarking & AI-text detection

MixForensics: Blend Before You Encode for Generalizable AI-Generated Video Detection

Ruiqi Liu, ZiAn Wang, Ruoxin Chen, Xuehai Bai and 5 more

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

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lenient 2/5
medium 1/10
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NeurIPS 2026The Hong Kong PolytechnicSingapore ManagementNanyang TechnologicalJilinHong Kong PolytechnicLLM pretraining & scaling laws

Language Models Demand New Computer Science

Chang Yang, Xinrun Wang, Shuxin Li, Qinggang Zhang and 4 more

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

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NeurIPS 2026JinanJilinDalian University of TechnologyAI in education

An Information-Theoretic Evaluation Framework for Benchmark and Model Diagnosis in Knowledge Tracing

Houru Jiang, Zixi Wang, Tengteng Cheng, Xueyi Li 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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NeurIPS 2026TongjiShanghai JiaotongJilinUNIVERSITY OF CALIFORNIA, SANTA Graph neural networks

Test-Time Graph Recalibration: Enhancing Robust Zero-Shot Inference for Graph Foundation Models

Chunchun Chen, Zhen Luo, Xing Wei, Yuxing Zhang and 4 more

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

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78%Highly rated
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NeurIPS 2026The Hong Kong University of ScieJilinHKUST-GZHong Kong University of Science Hallucination & factuality

Geometry-Calibrated Conformal Abstention for Language Models

Conformal Abstention uses geometry-calibrated confidence to decide abstention with finite-sample correctness guarantees, achieving 75% conditional correctness.

Rui Xu, Yi Chen, Sihong Xie, Hui Xiong

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

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lenient 5/5
medium 6/10
strict 0/5
72%Highly rated
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NeurIPS 2026JilinImmunocan BiotechTsinghuaHong Kong University of Science Nanyang TechnologicalProteins

ProteinOPD: Towards Effective and Efficient Preference Alignment for Protein Design

ProteinOPD balances multi-objective protein preferences via on-policy distillation from preference-specific teachers, preserving designability with 8x training speedup over RL methods.

Yulin Zhang, He CAO, Zihao Jiang, Chenyi Zi and 5 more

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

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lenient 4/5
medium 4/10
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88%Must read
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NeurIPS 2026Huazhong University of Science aInstitute of automation, ChineseJilinInstitute of Automation, ChineseCarnegie MellonVideo understanding

Rethinking the Readout: Unlocking Video Backbones for AI-Generated Video Detection

Standard video backbone readouts suppress patch-level temporal dynamics needed to detect AI-generated videos; a lightweight velocity-gated patch profiling readout reaches 95.28 AUC on frozen backbones.

Manni Cui, Ziheng Qin, ZiAn Wang, Ruiqi Liu and 7 more

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

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 1/5
76%Highly rated
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NeurIPS 2026JilinRIKEN-AIPThe University of WarwickRIKENRIKEN / University of TokyoInstruction tuning

Estimating and Orthogonalizing Unknown Pre-training Gradients for Continual Fine-tuning of Large Language Models

EoupCT estimates unknown pre-training gradients via learnable pseudo-data prompts and orthogonalizes updates to preserve general knowledge during continual LLM fine-tuning.

Bing Wang, Changchun Li, Xin-Qiang Cai, Lin Y Wu 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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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
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71%Highly rated
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NeurIPS 2026Jilin University, ChinaJilinThe University of SydneyCity, University of London, UKAGH University of Science and TeFlow matching

Disentangled Representation Learning via Flow Matching

A flow matching framework learns disentangled representations via factor-conditioned flows and orthogonality regularization, improving disentanglement, controllability, and sample fidelity over diffusion baselines.

Jinjin Chi, Taoping Liu, Mengtao Yin, Ximing Li and 4 more

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

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lenient 4/5
medium 3/10
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86%Must read
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NeurIPS 2026Beijing Institute of TechnologyRenmin University of ChinaHeriot-WattShenzhen Institutes of Advanced Microsoft ResearchModel-based RL

SLOPE: Optimistic Potential Landscape Shaping for Model-based Reinforcement Learning

SLOPE constructs optimistic potential landscapes via distributional regression to amplify sparse success signals and guide planning, outperforming baselines across sparse reward benchmarks.

Yao-Hui Li, Zeyu Wang, Xin Li, Wei Pang and 6 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 5/5
medium 7/10
strict 2/5
91%Must read
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NeurIPS 2026Royal Melbourne Institute of TecRMITU MelbourneJilinNanyang TechnologicalMechanistic interpretability

The Commit-Abstain Circuit: Why Language Models Hallucinate Instead of Abstaining

Mechanistic analysis reveals a Commit-Abstain Circuit where early commitment signals overpower later abstention corrections, causing hallucinations; training on its activations improves abstention accuracy by 12.2 points.

Gavin Vy Nguyen, Ziqi Xu, Jeffrey Chan, Estrid He 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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lenient 4/5
medium 9/10
strict 4/5
80%Must read
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NeurIPS 2026JilinShanghai Jiao TongByteDance Inc.The University of SydneyU SydneyVision-language models

EasyLens: A Training-Free Plug-and-Play Subtle-Lesion Representation Amplifier for Medical Vision-Language Models

EasyLens is a training-free plug-and-play module that amplifies subtle lesion representations in frozen medical vision-language models via prototype-based patch selection and morphology-guided residual enhancement, improving detection across datasets.

QIWEI ZENG, Hao Wang, Jinghao Lin, Shuchang Ye 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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AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5
78%Highly rated
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NeurIPS 2026JilinOcean University of ChinaPhysics-informed ML & PDEs

Neural Preconditioned Born Series: A Metric-Matched Framework for Learning-based Preconditioners

NPBS learns Born-series preconditioners in residual coordinates with metric-matched training, reducing Helmholtz iterations up to 1.9× versus direct residual learning and over 20× versus classical CBS.

Juntao Wang, Jiwei Jia, Xinliang Liu

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

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lenient 2/5
medium 7/10
strict 2/5
83%Must read
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NeurIPS 2026JilinAdelaideRMITJinanRoyal Melbourne Institute of TecDynamic graphs

UFO: A Unified Flow-Oriented Framework for Robust Continual Graph Learning

UFO proposes a flow-oriented continual graph learning framework that combats catastrophic forgetting and noisy-label-induced catastrophic remembering via generative replay and instance reliability scoring, outperforming baselines across benchmarks.

Danhui Zhang, Zhe Wang, Qing Qing, Jiarui Liu 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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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 0/5