1 citations · 1 across the 8 of their papers we have counts for
6 papers · 1 filter
LimRank: Less is More for Reasoning-Intensive Information Reranking
Tingyu Song, Yilun Zhao, Siyue Zhang +2
Existing approaches typically rely on large-scale fine-tuning to adapt LLMs for information reranking tasks, which is computationally expensive. In this work, we demonstrate that m…
FinLFQA: Evaluating Attributed Text Generation of LLMs in Financial Long-Form Question Answering
Yitao Long, Tiansheng Hu, Yilun Zhao +2
Large Language Models (LLMs) frequently hallucinate to long-form questions, producing plausible yet factually incorrect answers. A common mitigation strategy is to provide attribut…
SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks
Yilun Zhao, Kaiyan Zhang, Tiansheng Hu +15
We present SciArena, an open and collaborative platform for evaluating foundation models on scientific literature-grounded tasks. Unlike traditional benchmarks for scientific liter…
SUCEA: Reasoning-Intensive Retrieval for Adversarial Fact-checking through Claim Decomposition and Editing
Hongjun Liu, Yilun Zhao, Arman Cohan +1
Automatic fact-checking has recently received more attention as a means of combating misinformation. Despite significant advancements, fact-checking systems based on retrieval-augm…
MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Search
Yunhai Hu, Yilun Zhao, Chen Zhao +1
We introduce MCTS-RAG, a novel approach that enhances the reasoning capabilities of small language models on knowledge-intensive tasks by leveraging retrieval-augmented generation…
FinDVer: Explainable Claim Verification over Long and Hybrid-Content Financial Documents
Yilun Zhao, Yitao Long, Yuru Jiang +7
We introduce FinDVer, a comprehensive benchmark specifically designed to evaluate the explainable claim verification capabilities of LLMs in the context of understanding and analyz…