Most Cited COLM "parallelization techniques" Papers
418 papers found • Page 3 of 3
Conference
On Mechanistic Circuits for Extractive Question-Answering
Samyadeep Basu, Vlad I Morariu, Ryan A. Rossi et al.
Yourbench: Dynamic Evaluation Set Generation with LLMs
Sumuk Shashidhar, Clémentine Fourrier, Alina Lozovskaya et al.
Evaluating Large Language Models as Expert Annotators
Yu-Min Tseng, Wei-Lin Chen, Chung-Chi Chen et al.
KVSink: Understanding and Enhancing the Preservation of Attention Sinks in KV Cache Quantization for LLMs
Zunhai Su, Kehong Yuan
BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity
Chenyang Song, Weilin Zhao, Xu Han et al.
Partial Perspectives: How LLMs Handle Logically Inconsistent Knowledge in Reasoning Tasks
Zichao Li, Ines Arous, Jackie CK Cheung
NoWag: A Unified Framework for Shape Preserving Com- pression of Large Language Models
Lawrence Ray Liu, Inesh Chakrabarti, Yixiao Li et al.
FineMedLM-o1: Enhancing Medical Knowledge Reasoning Ability of LLM from Supervised Fine-Tuning to Test-Time Training
hongzhou yu, Tianhao Cheng, Yingwen Wang et al.
Teaching Models to Understand (but not Generate) High-risk Data
Ryan Yixiang Wang, Matthew Finlayson, Luca Soldaini et al.
Extragradient Preference Optimization (EGPO): Beyond Last-Iterate Convergence for Nash Learning from Human Feedback
Runlong Zhou, Maryam Fazel, Simon Shaolei Du
Analyzing Multilingualism in Large Language Models with Sparse Autoencoders
Ikhyun Cho, Julia Hockenmaier
CoLa: Learning to Interactively Collaborate with Large Language Models
Abhishek Sharma, Dan Goldwasser
HyperINF: Unleashing the HyperPower of Schulz's Method for Data Influence Estimation
Xinyu Zhou, Simin Fan, Martin Jaggi
G1yphD3c0de: Towards Safer Language Models on Visually Perturbed Texts
Yejinchoi, Yejin Yeo, Yejin Son et al.
Society of Mind Meets Real-Time Strategy: A Hierarchical Multi-Agent Framework for Strategic Reasoning
Daechul Ahn, San Kim, Jonghyun Choi
Rethinking Associative Memory Mechanism in Induction Head
Shuo Wang, Issei Sato
The Devil is in the EOS: Sequence Training for Detailed Image Captioning
Abdelrahman Mohamed, Yova Kementchedjhieva
CRABS: A syntactic-semantic pincer strategy for bounding LLM interpretation of Python notebooks
Meng Li, Timothy M. McPhillips, Dingmin Wang et al.