activity
20152026
most citedDocument Context Language Models

64 citations · 67 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

PERSONA: Dynamic and Compositional Inference-Time Personality Control via Activation Vector Algebra

Xiachong Feng, Liang Zhao, Weihong Zhong +5

Current methods for personality control in Large Language Models rely on static prompting or expensive fine-tuning, failing to capture the dynamic and compositional nature of human…

cs.LG2026

DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders

Xu Wang, Bingqing Jiang, Yu Wan +3

Sparse autoencoders (SAEs) have become a standard tool for mechanistic interpretability in autoregressive large language models (LLMs), enabling researchers to extract sparse, huma…

cs.CL2025

Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models

Kecheng Chen, Ziru Liu, Xijia Tao +7

Diffusion Language Models (DLMs) have recently achieved significant success due to their any-order generation capabilities. However, existing inference methods typically rely on lo…

cs.CL2025

Reasoning Path Divergence: A New Metric and Curation Strategy to Unlock LLM Diverse Thinking

Feng Ju, Zeyu Qin, Rui Min +3

While Test-Time Scaling (TTS) has proven effective in improving the reasoning ability of large language models (LLMs), low diversity in model outputs often becomes a bottleneck; th…

cs.LG2025

Teaching Language Models to Critique via Reinforcement Learning

Zhihui Xie, Jie Chen, Liyu Chen +3

Teaching large language models (LLMs) to critique and refine their outputs is crucial for building systems that can iteratively improve, yet it is fundamentally limited by the abil…

cs.CL2024★ 3 cited

Why Does the Effective Context Length of LLMs Fall Short?

Chenxin An, Jun Zhang, Ming Zhong +5

Advancements in distributed training and efficient attention mechanisms have significantly expanded the context window sizes of large language models (LLMs). However, recent work r…

cs.CL2024

FACTTRACK: Time-Aware World State Tracking in Story Outlines

Zhiheng Lyu, Kevin Yang, Lingpeng Kong +1

While accurately detecting and correcting factual contradictions in language model outputs has become increasingly important as their capabilities improve, doing so is highly chall…

cs.CL2015★ 64 cited

Document Context Language Models

Yangfeng Ji, Trevor Cohn, Lingpeng Kong +2

Text documents are structured on multiple levels of detail: individual words are related by syntax, but larger units of text are related by discourse structure. Existing language m…