184 citations · 220 across the 31 of their papers we have counts for
25 papers · 1 filter
SSR: Socratic Self-Refine for Large Language Model Reasoning
Haizhou Shi, Ye Liu, Bo Pang +6
Large Language Models (LLMs) have demonstrated remarkable reasoning abilities, yet existing test-time frameworks often rely on coarse self-verification and self-correction, limitin…
Retrofitting Small Multilingual Models for Retrieval: Matching 7B Performance with 300M Parameters
Lifu Tu, Yingbo Zhou, Semih Yavuz
Training effective multilingual embedding models presents unique challenges due to the diversity of languages and task objectives. Although small multilingual models (<1 B paramete…
Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings
Austin Xu, Srijan Bansal, Yifei Ming +2
The large language model (LLM)-as-judge paradigm has been used to meet the demand for a cheap, reliable, and fast evaluation of model outputs during AI system development and post-…
Investigating Factuality in Long-Form Text Generation: The Roles of Self-Known and Self-Unknown
Lifu Tu, Rui Meng, Shafiq Joty +2
Large language models (LLMs) have demonstrated strong capabilities in text understanding and generation. However, they often lack factuality, producing a mixture of true and false…
JudgeRank: Leveraging Large Language Models for Reasoning-Intensive Reranking
Tong Niu, Shafiq Joty, Ye Liu +3
Accurate document retrieval is crucial for the success of retrieval-augmented generation (RAG) applications, including open-domain question answering and code completion. While lar…
Traffic Light or Light Traffic? Investigating Phrasal Semantics in Large Language Models
Rui Meng, Ye Liu, Lifu Tu +3
Phrases are fundamental linguistic units through which humans convey semantics. This study critically examines the capacity of API-based large language models (LLMs) to comprehend…