26 papers
The Powerless Noise: How Experimental Settings Shape the Reported Power of Noise
MichaÅ Mazuryk, Fleur Dolmans, Louis Gehringer +3
Recent work has suggested that adding irrelevant documents to the input of retrieval-augmented generation (RAG) systems can improve question-answering performance, a phenomenon ref…
Improving the Efficiency and Effectiveness of LLM Knowledge Distillation for Conversational Search
Stan Fris, Jan Hutter, Jan Henrik Bertrand +2
Conversational Search (CS) considers retrieval of relevant documents based on conversational context. Large Language Models (LLMs) have significantly enhanced CS by enabling effect…
Hypencoder Revisited: Reproducibility and Analysis of Non-Linear Scoring for First-Stage Retrieval
Arne Eichholtz, Yongkang Li, Jutte Vijverberg +2
The Hypencoder, proposed by Killingback et al., is a retrieval framework that replaces the fixed inner-product scoring function used in standard bi-encoders with a query-specific n…
ChatR1: Reinforcement Learning for Conversational Reasoning and Retrieval Augmented Question Answering
Simon Lupart, Mohammad Aliannejadi, Evangelos Kanoulas
We present ChatR1, a reasoning framework based on reinforcement learning (RL) for conversational question answering (CQA). Reasoning plays an important role in CQA, where user inte…
Total Recall QA: A Verifiable Evaluation Suite for Deep Research Agents
Mahta Rafiee, Heydar Soudani, Zahra Abbasiantaeb +3
Deep research agents have emerged as LLM-based systems designed to perform multi-step information seeking and reasoning over large, open-domain sources to answer complex questions…
RAVENEA: A Benchmark for Multimodal Retrieval-Augmented Visual Culture Understanding
Jiaang Li, Yifei Yuan, Wenyan Li +8
As vision-language models (VLMs) become increasingly integrated into daily life, the need for accurate visual culture understanding is becoming critical. Yet, these models frequent…