3 citations · 8 across the 5 of their papers we have counts for
5 papers
Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning
Yu Xia, Zhouhang Xie, Xin Xu +4
Large language models improve final-answer accuracy through extended chain-of-thought reasoning, but often spend tokens inefficiently and offer little inference-time control. Exist…
Improving In-Context Learning with Reasoning Distillation
Nafis Sadeq, Xin Xu, Zhouhang Xie +4
Language models rely on semantic priors to perform in-context learning, which leads to poor performance on tasks involving inductive reasoning. Instruction-tuning methods based on…
Mitigating Hallucination in Fictional Character Role-Play
Nafis Sadeq, Zhouhang Xie, Byungkyu Kang +3
Role-playing has wide-ranging applications in customer support, embodied agents, and computational social science. The influence of parametric world knowledge of large language mod…
LLM+Reasoning+Planning for Supporting Incomplete User Queries in Presence of APIs
Sudhir Agarwal, Anu Sreepathy, David H. Alonso +1
Recent availability of Large Language Models (LLMs) has led to the development of numerous LLM-based approaches aimed at providing natural language interfaces for various end-user…
Unsupervised Improvement of Factual Knowledge in Language Models
Nafis Sadeq, Byungkyu Kang, Prarit Lamba +1
Masked language modeling (MLM) plays a key role in pretraining large language models. But the MLM objective is often dominated by high-frequency words that are sub-optimal for lear…