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20232026
most citedQuam: Adaptive Retrieval through Query Affinity Modelling

7 citations · 12 across the 16 of their papers we have counts for

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cs.CL2025

Trust but Verify! A Survey on Verification Design for Test-time Scaling

V Venktesh, Mandeep Rathee, Avishek Anand

Test-time scaling (TTS) has emerged as a new frontier for scaling the performance of Large Language Models. In test-time scaling, by using more computational resources during infer…

cs.CL2025

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…

cs.CL2025

It's High Time: A Survey of Temporal Question Answering

Bhawna Piryani, Abdelrahman Abdallah, Jamshid Mozafari +2

Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Temporal Question Answering (TQA), a…

cs.CL2025

A Study into Investigating Temporal Robustness of LLMs

Jonas Wallat, Abdelrahman Abdallah, Adam Jatowt +1

Large Language Models (LLMs) encapsulate a surprising amount of factual world knowledge. However, their performance on temporal questions and historical knowledge is limited becaus…

cs.CL2024★ 3 cited

Correctness is not Faithfulness in RAG Attributions

Jonas Wallat, Maria Heuss, Maarten de Rijke +1

Retrieving relevant context is a common approach to reduce hallucinations and enhance answer reliability. Explicitly citing source documents allows users to verify generated respon…