4 papers · 1 filter
KCS: Diversify Multi-hop Question Generation with Knowledge Composition Sampling
Yangfan Wang, Jie Liu, Chen Tang +2
Multi-hop question answering faces substantial challenges due to data sparsity, which increases the likelihood of language models learning spurious patterns. To address this issue,…
Reasoning Under Uncertainty: Exploring Probabilistic Reasoning Capabilities of LLMs
Mobina Pournemat, Keivan Rezaei, Gaurang Sriramanan +5
Despite widespread success in language understanding and generation, large language models (LLMs) exhibit unclear and often inconsistent behavior when faced with tasks that require…
Evaluating Quality of Answers for Retrieval-Augmented Generation: A Strong LLM Is All You Need
Yang Wang, Alberto Garcia Hernandez, Roman Kyslyi +1
We present a comprehensive study of answer quality evaluation in Retrieval-Augmented Generation (RAG) applications using vRAG-Eval, a novel grading system that is designed to asses…
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Rada Mihalcea
As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks. However, LLMs a…