AgentIR: Reasoning-Aware Retrieval for Deep Research Agents
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Zijian, Ma, Xueguang, Zhuang, Shengyao, Lin, Jimmy, Asai, Akari, Zhong, Victor |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning
by: Zhuang, Shengyao, et al.
Published: (2025)
by: Zhuang, Shengyao, et al.
Published: (2025)
ORBIT: Scalable and Verifiable Data Generation for Search Agents on a Tight Budget
by: Thakur, Nandan, et al.
Published: (2026)
by: Thakur, Nandan, et al.
Published: (2026)
LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum
by: Xu, Zhichao, et al.
Published: (2026)
by: Xu, Zhichao, et al.
Published: (2026)
BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent
by: Chen, Zijian, et al.
Published: (2025)
by: Chen, Zijian, et al.
Published: (2025)
Hard Negatives, Hard Lessons: Revisiting Training Data Quality for Robust Information Retrieval with LLMs
by: Thakur, Nandan, et al.
Published: (2025)
by: Thakur, Nandan, et al.
Published: (2025)
DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers
by: Ma, Xueguang, et al.
Published: (2025)
by: Ma, Xueguang, et al.
Published: (2025)
Train for Truth, Keep the Skills: Binary Retrieval-Augmented Reward Mitigates Hallucinations
by: Chen, Tong, et al.
Published: (2025)
by: Chen, Tong, et al.
Published: (2025)
PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval
by: Zhuang, Shengyao, et al.
Published: (2024)
by: Zhuang, Shengyao, et al.
Published: (2024)
VISA: Retrieval Augmented Generation with Visual Source Attribution
by: Ma, Xueguang, et al.
Published: (2024)
by: Ma, Xueguang, et al.
Published: (2024)
MAGMaR Shared Task System Description: Video Retrieval with OmniEmbed
by: Zhan, Jiaqi Samantha, et al.
Published: (2025)
by: Zhan, Jiaqi Samantha, et al.
Published: (2025)
LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs
by: Jiang, Ziyan, et al.
Published: (2024)
by: Jiang, Ziyan, et al.
Published: (2024)
MemReranker: Reasoning-Aware Reranking for Agent Memory Retrieval
by: Li, Chunyu, et al.
Published: (2026)
by: Li, Chunyu, et al.
Published: (2026)
Rethinking On-policy Optimization for Query Augmentation
by: Xu, Zhichao, et al.
Published: (2025)
by: Xu, Zhichao, et al.
Published: (2025)
Document Screenshot Retrievers are Vulnerable to Pixel Poisoning Attacks
by: Zhuang, Shengyao, et al.
Published: (2025)
by: Zhuang, Shengyao, et al.
Published: (2025)
Reliable, Adaptable, and Attributable Language Models with Retrieval
by: Asai, Akari, et al.
Published: (2024)
by: Asai, Akari, et al.
Published: (2024)
Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies
by: Zhang, Ming, et al.
Published: (2026)
by: Zhang, Ming, et al.
Published: (2026)
Found in the Middle: Permutation Self-Consistency Improves Listwise Ranking in Large Language Models
by: Tang, Raphael, et al.
Published: (2023)
by: Tang, Raphael, et al.
Published: (2023)
SAGE: Benchmarking and Improving Retrieval for Deep Research Agents
by: Hu, Tiansheng, et al.
Published: (2026)
by: Hu, Tiansheng, et al.
Published: (2026)
2D Matryoshka Training for Information Retrieval
by: Wang, Shuai, et al.
Published: (2024)
by: Wang, Shuai, et al.
Published: (2024)
General-Reasoner: Advancing LLM Reasoning Across All Domains
by: Ma, Xueguang, et al.
Published: (2025)
by: Ma, Xueguang, et al.
Published: (2025)
TRACE: Trajectory-Aware Comprehensive Evaluation for Deep Research Agents
by: Chen, Yanyu, et al.
Published: (2026)
by: Chen, Yanyu, et al.
Published: (2026)
Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems
by: Zhuang, Shengyao, et al.
Published: (2024)
by: Zhuang, Shengyao, et al.
Published: (2024)
FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation
by: Wang, Shuai, et al.
Published: (2024)
by: Wang, Shuai, et al.
Published: (2024)
Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality
by: Ma, Xueguang, et al.
Published: (2025)
by: Ma, Xueguang, et al.
Published: (2025)
Out of Style: RAG's Fragility to Linguistic Variation
by: Cao, Tianyu, et al.
Published: (2025)
by: Cao, Tianyu, et al.
Published: (2025)
WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models
by: Wang, Rui, et al.
Published: (2025)
by: Wang, Rui, et al.
Published: (2025)
An Early FIRST Reproduction and Improvements to Single-Token Decoding for Fast Listwise Reranking
by: Chen, Zijian, et al.
Published: (2024)
by: Chen, Zijian, et al.
Published: (2024)
SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning
by: Zheng, Tianshi, et al.
Published: (2026)
by: Zheng, Tianshi, et al.
Published: (2026)
CodeRAG-Bench: Can Retrieval Augment Code Generation?
by: Wang, Zora Zhiruo, et al.
Published: (2024)
by: Wang, Zora Zhiruo, et al.
Published: (2024)
PixelWorld: How Far Are We from Perceiving Everything as Pixels?
by: Lyu, Zhiheng, et al.
Published: (2025)
by: Lyu, Zhiheng, et al.
Published: (2025)
Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answering
by: Wang, Yubo, et al.
Published: (2023)
by: Wang, Yubo, et al.
Published: (2023)
Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki
by: Ming, Haoliang, et al.
Published: (2026)
by: Ming, Haoliang, et al.
Published: (2026)
ReasonIR: Training Retrievers for Reasoning Tasks
by: Shao, Rulin, et al.
Published: (2025)
by: Shao, Rulin, et al.
Published: (2025)
History-Aware Reasoning for GUI Agents
by: Wang, Ziwei, et al.
Published: (2025)
by: Wang, Ziwei, et al.
Published: (2025)
AgentExpt: Automating AI Experiment Design with LLM-based Resource Retrieval Agent
by: Li, Yu, et al.
Published: (2025)
by: Li, Yu, et al.
Published: (2025)
Large Language Models for Stemming: Promises, Pitfalls and Failures
by: Wang, Shuai, et al.
Published: (2024)
by: Wang, Shuai, et al.
Published: (2024)
Cost-Aware Retrieval-Augmentation Reasoning Models with Adaptive Retrieval Depth
by: Hashemi, Helia, et al.
Published: (2025)
by: Hashemi, Helia, et al.
Published: (2025)
LineRetriever: Planning-Aware Observation Reduction for Web Agents
by: Kerboua, Imene, et al.
Published: (2025)
by: Kerboua, Imene, et al.
Published: (2025)
Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning
by: Tang, Yihong, et al.
Published: (2025)
by: Tang, Yihong, et al.
Published: (2025)
FinDeepResearch: Evaluating Deep Research Agents in Rigorous Financial Analysis
by: Zhu, Fengbin, et al.
Published: (2025)
by: Zhu, Fengbin, et al.
Published: (2025)
Similar Items
-
Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning
by: Zhuang, Shengyao, et al.
Published: (2025) -
ORBIT: Scalable and Verifiable Data Generation for Search Agents on a Tight Budget
by: Thakur, Nandan, et al.
Published: (2026) -
LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum
by: Xu, Zhichao, et al.
Published: (2026) -
BrowseComp-Plus: A More Fair and Transparent Evaluation Benchmark of Deep-Research Agent
by: Chen, Zijian, et al.
Published: (2025) -
Hard Negatives, Hard Lessons: Revisiting Training Data Quality for Robust Information Retrieval with LLMs
by: Thakur, Nandan, et al.
Published: (2025)