3 papers
cs.IR2026
FRESCO: Benchmarking and Optimizing Re-rankers for Evolving Semantic Conflict in Retrieval-Augmented Generation
Sohyun An, Hayeon Lee, Shuibenyang Yuan +4
Retrieval-Augmented Generation (RAG) is a key approach to mitigating the temporal staleness of large language models (LLMs) by grounding responses in up-to-date evidence. Within th…
cs.AI2026
Cycle-Consistent Search: Question Reconstructability as a Proxy Reward for Search Agent Training
Sohyun An, Shuibenyang Yuan, Hayeon Lee +2
Reinforcement Learning (RL) has shown strong potential for optimizing search agents in complex information retrieval tasks. However, existing approaches predominantly rely on gold…
cs.LG2024
Diffusion-Based Neural Network Weights Generation
Bedionita Soro, Bruno Andreis, Hayeon Lee +4
Transfer learning has gained significant attention in recent deep learning research due to its ability to accelerate convergence and enhance performance on new tasks. However, its…