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Matching papers

ABSeeker: Training Long-Horizon Search Agents via Answer-Backtracked Credit Assignment

63 upvotes · 5 AUG 2026 · Yijun Lu, Rui Ye, Jiajun Wang et al.

This paper proposes a new method for training long-horizon search agents that can search, retrieve, and integrate evidence to reach a final answer. Practitioners in natural language processing and AI research might care about this paper because it shows a way to improve the performance of search agents, which can be used in applications such as question-answering systems.

reinforcement learningsearch agentscredit assignmentnatural language processinglong-horizon planning

Iris: Climbing to the Search Frontier

53 upvotes · 3 SEP 2026 · Ziyuan Liu, Hengqi Liu, Zichuan Wang et al.

This paper presents two search agents, Iris-mini and Iris-pro, trained to solve complex search tasks using reinforcement learning and self-supervised learning. Practitioners might care because these models achieve state-of-the-art results on various benchmarks, demonstrating the potential of AI-powered search agents in real-world applications.

continual learningsearch agentsreinforcement learningnatural language processingbenchmarks