Imagen de Portada

Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Jin, Bowen, Zeng, Hansi, Yue, Zhenrui, Yoon, Jinsung, Arik, Sercan, Wang, Dong, Zamani, Hamed, Han, Jiawei
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language Artificial Intelligence Information Retrieval
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

An Empirical Study on Reinforcement Learning for Reasoning-Search Interleaved LLM Agents
por: Jin, Bowen, et al.
Publicado: (2025)

CoSearch: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search
por: Zeng, Hansi, et al.
Publicado: (2026)

Scaling Sparse and Dense Retrieval in Decoder-Only LLMs
por: Zeng, Hansi, et al.
Publicado: (2025)

Retrieval Augmented Time Series Forecasting
por: Han, Sungwon, et al.
Publicado: (2025)

Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding
por: Zeng, Hansi, et al.
Publicado: (2024)

Hypencoder: Hypernetworks for Information Retrieval
por: Killingback, Julian, et al.
Publicado: (2025)

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
por: Jin, Bowen, et al.
Publicado: (2025)

Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models
por: Salemi, Alireza, et al.
Publicado: (2024)

TARSE: Test-Time Adaptation via Retrieval of Skills and Experience for Reasoning Agents
por: Wang, Junda, et al.
Publicado: (2026)

Structure-R1: Dynamically Leveraging Structural Knowledge in LLM Reasoning through Reinforcement Learning
por: Wu, Junlin, et al.
Publicado: (2025)

Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning
por: Mo, Fengran, et al.
Publicado: (2026)

LESER: Learning to Expand via Search Engine-feedback Reinforcement in e-Commerce
por: Zhang, Yipeng, et al.
Publicado: (2025)

Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications
por: Tavakoli, Leila, et al.
Publicado: (2025)

Online and Offline Evaluation in Search Clarification
por: Tavakoli, Leila, et al.
Publicado: (2024)

Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback
por: Alam, Md Zarif Ul, et al.
Publicado: (2026)

Middleman Bias in Advertising: Aligning Relevance of Keyphrase Recommendations with Search
por: Dey, Soumik, et al.
Publicado: (2025)

DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning
por: Jiang, Pengcheng, et al.
Publicado: (2025)

Train Once, Deploy Anywhere: Matryoshka Representation Learning for Multimodal Recommendation
por: Wang, Yueqi, et al.
Publicado: (2024)

Uncertainty Quantification for Retrieval-Augmented Reasoning
por: Soudani, Heydar, et al.
Publicado: (2025)

Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG
por: Jin, Bowen, et al.
Publicado: (2024)

Retrieval Augmented Conversational Recommendation with Reinforcement Learning
por: Yue, Zhenrui, et al.
Publicado: (2026)

Distillation and Refinement of Reasoning in Small Language Models for Document Re-ranking
por: Samarinas, Chris, et al.
Publicado: (2025)

Federated Recommendation via Hybrid Retrieval Augmented Generation
por: Zeng, Huimin, et al.
Publicado: (2024)

Bridging Personalization and Control in Scientific Personalized Search
por: Mysore, Sheshera, et al.
Publicado: (2024)

Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning
por: Li, Jinzheng, et al.
Publicado: (2025)

Matlas: A Semantic Search Engine for Mathematics
por: Ju, Haocheng, et al.
Publicado: (2026)

Caption Injection for Optimization in Generative Search Engine
por: Chen, Xiaolu, et al.
Publicado: (2025)

PseudoSeer: a Search Engine for Pseudocode
por: Toksoz, Levent, et al.
Publicado: (2024)

ConvSearch-R1: Enhancing Query Reformulation for Conversational Search with Reasoning via Reinforcement Learning
por: Zhu, Changtai, et al.
Publicado: (2025)

ProCIS: A Benchmark for Proactive Retrieval in Conversations
por: Samarinas, Chris, et al.
Publicado: (2024)

TongSearch-QR: Reinforced Query Reasoning for Retrieval
por: Qin, Xubo, et al.
Publicado: (2025)

Introducing Semantic Capability in LinkedIn's Content Search Engine
por: Yang, Xin, et al.
Publicado: (2024)

AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play
por: Xu, Ran, et al.
Publicado: (2025)

CIIR@LiveRAG 2025: Optimizing Multi-Agent Retrieval Augmented Generation through Self-Training
por: Salemi, Alireza, et al.
Publicado: (2025)

Controlling Output Rankings in Generative Engines for LLM-based Search
por: Jin, Haibo, et al.
Publicado: (2026)

Smart Sentiment Analysis-based Search Engine Classification Intelligence
por: Nkongolo, Mike
Publicado: (2023)

Bayesian Rational Search Engine User
por: Ma, Shichao
Publicado: (2026)

BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
por: Su, Hongjin, et al.
Publicado: (2024)

Truncated Step-Level Sampling with Process Rewards for Retrieval-Augmented Reasoning
por: Samarinas, Chris, et al.
Publicado: (2026)

ParallelSearch: Train your LLMs to Decompose Query and Search Sub-queries in Parallel with Reinforcement Learning
por: Zhao, Shu, et al.
Publicado: (2025)