184 citations · 582 across the 57 of their papers we have counts for
8 papers · 1 filter
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…
CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval
Ye Liu, Rui Meng, Shafiq Joty +4
Despite the success of text retrieval in many NLP tasks, code retrieval remains a largely underexplored area. Most text retrieval systems are tailored for natural language queries,…
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…
P-FOLIO: Evaluating and Improving Logical Reasoning with Abundant Human-Written Reasoning Chains
Simeng Han, Aaron Yu, Rui Shen +13
Existing methods on understanding the capabilities of LLMs in logical reasoning rely on binary entailment classification or synthetically derived rationales, which are not sufficie…
Improving LLM Reasoning through Scaling Inference Computation with Collaborative Verification
Zhenwen Liang, Ye Liu, Tong Niu +3
Despite significant advancements in the general capability of large language models (LLMs), they continue to struggle with consistent and accurate reasoning, especially in complex…
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…
VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks
Ziyan Jiang, Rui Meng, Xinyi Yang +3
Embedding models have been crucial in enabling various downstream tasks such as semantic similarity, information retrieval, and clustering. Recently, there has been a surge of inte…
Parameter-Efficient Detoxification with Contrastive Decoding
Tong Niu, Caiming Xiong, Semih Yavuz +1
The field of natural language generation has witnessed significant advancements in recent years, including the development of controllable text generation techniques. However, cont…