2025 "large language models" Papers
416 papers found • Page 8 of 9
Stop DDoS Attacking the Research Community with AI-Generated Survey Papers
Jianghao Lin, Rong Shan, Jiachen Zhu et al.
Straight to Zero: Why Linearly Decaying the Learning Rate to Zero Works Best for LLMs
Shane Bergsma, Nolan Dey, Gurpreet Gosal et al.
Streaming Attention Approximation via Discrepancy Theory
Ekaterina Kochetkova, Kshiteej Jitesh Sheth, Insu Han et al.
Streamlining Redundant Layers to Compress Large Language Models
Xiaodong Chen, Yuxuan Hu, Jing Zhang et al.
StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization
Zhuoqun Li, Xuanang Chen, Haiyang Yu 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
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 Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
Tian Jin, Ahmed Imtiaz Humayun, Utku Evci et al.
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
Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models
Chengyu Du, Jinyi Han, Yizhou Ying et al.
Timely Clinical Diagnosis through Active Test Selection
Silas Ruhrberg Estévez, Nicolás Astorga, Mihaela van der Schaar
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Zayne Sprague, Fangcong Yin, Juan Rodriguez et al.
Token-Level Self-Play with Importance-Aware Guidance for Large Language Models
Tue Le, Hoang Tran, Quyen Tran et al.
TorchTitan: One-stop PyTorch native solution for production ready LLM pretraining
Wanchao Liang, Tianyu Liu, Less Wright et al.
Towards a Theoretical Understanding of Synthetic Data in LLM Post-Training: A Reverse-Bottleneck Perspective
Zeyu Gan, Yong Liu
Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
Qizhou Wang, Bo Han, Puning Yang et al.
Towards Federated RLHF with Aggregated Client Preference for LLMs
Feijie Wu, Xiaoze Liu, Haoyu Wang et al.
Towards Higher Effective Rank in Parameter-Efficient Fine-tuning using Khatri-Rao Product
Paul Albert, Frederic Zhang, Hemanth Saratchandran et al.
Towards Optimal Multi-draft Speculative Decoding
Zhengmian Hu, Tong Zheng, Vignesh Viswanathan et al.
Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs
Sungmin Cha, Sungjun Cho, Dasol Hwang et al.
Towards Understanding Safety Alignment: A Mechanistic Perspective from Safety Neurons
Jianhui Chen, Xiaozhi Wang, Zijun Yao et al.
Toward Understanding In-context vs. In-weight Learning
Bryan Chan, Xinyi Chen, Andras Gyorgy et al.
Training-Free Activation Sparsity in Large Language Models
James Liu, Pragaash Ponnusamy, Tianle Cai 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.
Trajectory-LLM: A Language-based Data Generator for Trajectory Prediction in Autonomous Driving
Kairui Yang, Zihao Guo, Gengjie Lin et al.
Tree of Preferences for Diversified Recommendation
Hanyang Yuan, Ning Tang, Tongya Zheng 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.
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
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.
UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models
Xin Xu, Jiaxin ZHANG, Tianhao Chen et al.
Understanding Parametric and Contextual Knowledge Reconciliation within Large Language Models
Jun Zhao, Yongzhuo Yang, Xiang Hu 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.
Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
Xiaoyu Wu, Yifei Pang, Terrance Liu et al.
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
Tianci Liu, Ruirui Li, Yunzhe Qi et al.
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning
Gangwei Jiang, caigao jiang, Zhaoyi Li et al.
Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment
Yuze Zhao, Tianyun Ji, Wenjun Feng et al.
U-shaped and Inverted-U Scaling behind Emergent Abilities of Large Language Models
Tung-Yu Wu, Melody Lo
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.