5 papers
Think Right, Not More: Test-Time Scaling for Numerical Claim Verification
Primakov Chungkham, V Venktesh, Vinay Setty +1
Fact-checking real-world claims, particularly numerical claims, is inherently complex that require multistep reasoning and numerical reasoning for verifying diverse aspects of the…
Test-time Corpus Feedback: From Retrieval to RAG
Mandeep Rathee, V Venktesh, Sean MacAvaney +1
Retrieval-Augmented Generation (RAG) has emerged as a standard framework for knowledge-intensive NLP tasks, combining large language models (LLMs) with document retrieval from exte…
Evaluating List Construction and Temporal Understanding capabilities of Large Language Models
Alexandru Dumitru, V Venktesh, Adam Jatowt +1
Large Language Models (LLMs) have demonstrated immense advances in a wide range of natural language tasks. However, these models are susceptible to hallucinations and errors on par…
Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets
Mandeep Rathee, V Venktesh, Sean MacAvaney +1
Advanced relevance models, such as those that use large language models (LLMs), provide highly accurate relevance estimations. However, their computational costs make them infeasib…
FactIR: A Real-World Zero-shot Open-Domain Retrieval Benchmark for Fact-Checking
Venktesh V, Vinay Setty
The field of automated fact-checking increasingly depends on retrieving web-based evidence to determine the veracity of claims in real-world scenarios. A significant challenge in t…