Poster "large language models" Papers
740 papers found • Page 10 of 15
Conference
SteerConf: Steering LLMs for Confidence Elicitation
Ziang Zhou, Tianyuan Jin, Jieming Shi et al.
Steering LLMs' Behavior with Concept Activation Vectors
Ruixuan HUANG, Shuai Wang
Steering When Necessary: Flexible Steering Large Language Models with Backtracking
Zifeng Cheng, Jinwei Gan, Zhiwei Jiang et al.
STEER-ME: Assessing the Microeconomic Reasoning of Large Language Models
Narun Raman, Taylor Lundy, Thiago Amin et al.
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Shengyu Feng, Xiang Kong, shuang ma 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.
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.
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.
TANGO: Training-free Embodied AI Agents for Open-world Tasks
Filippo Ziliotto, Tommaso Campari, Luciano Serafini et al.
Targeted control of fast prototyping through domain-specific interface
Yu-Zhe Shi, Mingchen Liu, Hanlu Ma et al.
TCM-Ladder: A Benchmark for Multimodal Question Answering on Traditional Chinese Medicine
Jiacheng Xie, Yang Yu, Ziyang Zhang et al.
The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text
Nikhil Kandpal, Brian Lester, Colin Raffel et al.
The Complexity of Learning Sparse Superposed Features with Feedback
Akash Kumar
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation
Fredrik Carlsson, Fangyu Liu, Daniel Ward 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 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.
ThinkBot: Embodied Instruction Following with Thought Chain Reasoning
Guanxing Lu, Ziwei Wang, Changliu Liu 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.
ToolACE: Winning the Points of LLM Function Calling
Weiwen Liu, Xu Huang, Xingshan Zeng 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.
Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction
Huawen Feng, ZekunYao, Junhao Zheng 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.
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.
Triples as the Key: Structuring Makes Decomposition and Verification Easier in LLM-based TableQA
Zhen Yang, Ziwei Du, Minghan Zhang et al.