NEURIPS "large language models" Papers
298 papers found • Page 6 of 6
SUMO: Subspace-Aware Moment-Orthogonalization for Accelerating Memory-Efficient LLM Training
Yehonathan Refael, Guy Smorodinsky, Tom Tirer et al.
SWE-bench Goes Live!
Linghao Zhang, Shilin He, Chaoyun Zhang et al.
SWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications
Jinyang Li, Xiaolong Li, Ge Qu et al.
SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
Junteng Liu, Yuanxiang Fan, Jiang Zhuo et al.
System Prompt Optimization with Meta-Learning
Yumin Choi, Jinheon Baek, Sung Ju Hwang
Table as a Modality for Large Language Models
Liyao Li, Chao Ye, Wentao Ye et al.
TANDEM: Bi-Level Data Mixture Optimization with Twin Networks
Jiaxing Wang, Deping Xiang, Jin Xu et al.
TCM-Ladder: A Benchmark for Multimodal Question Answering on Traditional Chinese Medicine
Jiacheng Xie, Yang Yu, Ziyang Zhang et al.
The Best Instruction-Tuning Data are Those That Fit
Dylan Zhang, Qirun Dai, Hao Peng
The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text
Nikhil Kandpal, Brian Lester, Colin Raffel et al.
The Right to Red-Team: Adversarial AI Literacy as a Civic Imperative in K-12 Education
Devan Walton, Haesol Bae
The Rise of Parameter Specialization for Knowledge Storage in Large Language Models
Yihuai Hong, Yiran Zhao, Wei Tang et al.
ThinkBench: Dynamic Out-of-Distribution Evaluation for Robust LLM Reasoning
Shulin Huang, Linyi Yang, Yan Song et al.
Thinker: Learning to Think Fast and Slow
Stephen Chung, Wenyu Du, Jie Fu
Timely Clinical Diagnosis through Active Test Selection
Silas Ruhrberg Estévez, Nicolás Astorga, Mihaela van der Schaar
Token-Level Self-Play with Importance-Aware Guidance for Large Language Models
Tue Le, Hoang Tran, Quyen Tran et al.
Towards Understanding Safety Alignment: A Mechanistic Perspective from Safety Neurons
Jianhui Chen, Xiaozhi Wang, Zijun Yao et al.
Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
Haizhou Shi, Yibin Wang, Ligong Han et al.
TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration
Yuwei Du, Jie Feng, Jie Zhao et al.
Transforming Generic Coder LLMs to Effective Binary Code Embedding Models for Similarity Detection
Litao Li, Leo Song, Steven Ding et al.
Traversal Verification for Speculative Tree Decoding
Yepeng Weng, Qiao Hu, Xujie Chen et al.
Tree of Preferences for Diversified Recommendation
Hanyang Yuan, Ning Tang, Tongya Zheng et al.
TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning
Sheng Wang, Pengan CHEN, Jingqi Zhou et al.
Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs
Yibo Wang, Hai-Long Sun, Guangda Huzhang et al.
Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
Xiaoyuan Liu, Tian Liang, Zhiwei He et al.
Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection
Herun Wan, Jiaying Wu, Minnan Luo et al.
TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks
Xiang Meng, Mehdi Makni, Rahul Mazumder
T-SHIRT: Token-Selective Hierarchical Data Selection for Instruction Tuning
Yanjun Fu, Faisal Hamman, Sanghamitra Dutta
TTRL: Test-Time Reinforcement Learning
Yuxin Zuo, Kaiyan Zhang, Li Sheng et al.
Týr-the-Pruner: Structural Pruning LLMs via Global Sparsity Distribution Optimization
Guanchen Li, Yixing Xu, Zeping Li et al.
Understanding Parametric and Contextual Knowledge Reconciliation within Large Language Models
Jun Zhao, Yongzhuo Yang, Xiang Hu et al.
UniEdit: A Unified Knowledge Editing Benchmark for Large Language Models
Qizhou Chen, Dakan Wang, Taolin Zhang et al.
Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models
Siwei Zhang, Yun Xiong, Yateng Tang et al.
Uni-LoRA: One Vector is All You Need
Kaiyang Li, Shaobo Han, Qing Su et al.
Universal Cross-Tokenizer Distillation via Approximate Likelihood Matching
Benjamin Minixhofer, Ivan Vulić, Edoardo Maria Ponti
Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
Xiaoyu Wu, Yifei Pang, Terrance Liu et al.
VADTree: Explainable Training-Free Video Anomaly Detection via Hierarchical Granularity-Aware Tree
Wenlong Li, Yifei Xu, Yuan Rao et al.
Valid Inference with Imperfect Synthetic Data
Yewon Byun, Shantanu Gupta, Zachary Lipton et al.
Variational Uncertainty Decomposition for In-Context Learning
I. Shavindra Jayasekera, Jacob Si, Filippo Valdettaro et al.
VERA: Variational Inference Framework for Jailbreaking Large Language Models
Anamika Lochab, Lu Yan, Patrick Pynadath et al.
Virus Infection Attack on LLMs: Your Poisoning Can Spread "VIA" Synthetic Data
Zi Liang, Qingqing Ye, Xuan Liu et al.
VT-FSL: Bridging Vision and Text with LLMs for Few-Shot Learning
Wenhao Li, Qiangchang Wang, Xianjing Meng et al.
What Happens During the Loss Plateau? Understanding Abrupt Learning in Transformers
Pulkit Gopalani, Wei Hu
What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models
Keyon Vafa, Sarah Bentley, Jon Kleinberg et al.
When Can Model-Free Reinforcement Learning be Enough for Thinking?
Josiah Hanna, Nicholas Corrado
Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation
Sungmin Cha, Kyunghyun Cho
Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search
Yuichi Inoue, Kou Misaki, Yuki Imajuku et al.
WritingBench: A Comprehensive Benchmark for Generative Writing
Yuning Wu, Jiahao Mei, Ming Yan et al.