Most Cited COLM "task vector fusion" Papers
418 papers found • Page 3 of 3
Conference
Enhancing LLM Reliability via Explicit Knowledge Boundary Modeling
Hang Zheng, Hongshen Xu, Yuncong Liu et al.
Effective Length Extrapolation via Dimension-Wise Positional Embeddings Manipulation
Yi Lu, Wanxu Zhao, Xin Zhou et al.
A Controlled Study on Long Context Extension and Generalization in LLMs
Yi Lu, Jing Nathan Yan, Songlin Yang et al.
Efficient Process Reward Model Training via Active Learning
Keyu Duan, Zichen Liu, Xin Mao et al.
FormaRL: Enhancing Autoformalization with no Labeled Data
Yanxing Huang, Xinling Jin, Sijie Liang et al.
ICQuant: Index Coding enables Low-bit LLM Quantization
Xinlin Li, Osama Hanna, Christina Fragouli et al.
MAC: A Live Benchmark for Multimodal Large Language Models in Scientific Understanding
Mohan Jiang, Jin Gao, Jiahao Zhan et al.
Interpreting the linear structure of vision-language model embedding spaces
Isabel Papadimitriou, Huangyuan Su, Thomas Fel et al.
LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models
Minqian Liu, Zhiyang Xu, Xinyi Zhang et al.
Establishing Task Scaling Laws via Compute-Efficient Model Ladders
Akshita Bhagia, Jiacheng Liu, Alexander Wettig et al.
Can A Society of Generative Agents Simulate Human Behavior and Inform Public Health Policy? A Case Study on Vaccine Hesitancy
Abe Bohan Hou, Hongru Du, Yichen Wang et al.
RARe: Retrieval Augmented Retrieval with In-Context Examples
Atula Tejaswi, Yoonsang Lee, sujay sanghavi et al.
PersonaEval: Are LLM Evaluators Human Enough to Judge Role-Play?
Lingfeng Zhou, Jialing Zhang, Jin Gao et al.
MapIQ: Evaluating Multimodal Large Language Models for Map Question Answering
Varun Srivastava, Fan Lei, Srija Mukhopadhyay et al.
Bayesian scaling laws for in-context learning
Aryaman Arora, Dan Jurafsky, Christopher Potts et al.
DoomArena: A framework for Testing AI Agents Against Evolving Security Threats
Léo Boisvert, Abhay Puri, Gabriel Huang et al.
Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time
Van Yang, Xiang Yue, Vipin Chaudhary et al.
Transformers are Efficient Compilers, Provably
Xiyu Zhai, Runlong Zhou, Liao Zhang et al.