6 papers
MERRIN: A Benchmark for Multimodal Evidence Retrieval and Reasoning in Noisy Web Environments
Han Wang, David Wan, Hyunji Lee +6
Motivated by the underspecified, multi-hop nature of search queries and the multimodal, heterogeneous, and often conflicting nature of real-world web results, we introduce MERRIN (…
CodaRAG: Connecting the Dots with Associativity Inspired by Complementary Learning
Cheng-Yen Li, Xuanjun Chen, Claire Lin +4
Large Language Models (LLMs) struggle with knowledge-intensive tasks due to hallucinations and fragmented reasoning over dispersed information. While Retrieval-Augmented Generation…
SealQA: Raising the Bar for Reasoning in Search-Augmented Language Models
Thinh Pham, Nguyen Nguyen, Pratibha Zunjare +3
We introduce SealQA, a new challenge benchmark for evaluating SEarch-Augmented Language models on fact-seeking questions where web search yields conflicting, noisy, or unhelpful re…
EvoSkill: Automated Skill Discovery for Multi-Agent Systems
Salaheddin Alzubi, Noah Provenzano, Jaydon Bingham +2
Coding agents are increasingly used as general-purpose problem solvers, but their flexibility does not by itself confer the domain expertise needed for specialized tasks. Recent wo…
PRISM: Pushing the Frontier of Deep Think via Process Reward Model-Guided Inference
Rituraj Sharma, Weiyuan Chen, Noah Provenzano +1
DEEPTHINK methods improve reasoning by generating, refining, and aggregating populations of candidate solutions, which enables strong performance on complex mathematical and scient…
ROMA: Recursive Open Meta-Agent Framework for Long-Horizon Multi-Agent Systems
Salaheddin Alzu'bi, Baran Nama, Arda Kaz +6
Current agentic frameworks underperform on long-horizon tasks. As reasoning depth increases, sequential orchestration becomes brittle, context windows impose hard limits that degra…