AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Ran, Zhuang, Yuchen, Dong, Zihan, Wang, Jonathan, Yu, Yue, Ho, Joyce C., Zhang, Linjun, Wang, Haoyu, Shi, Wenqi, Yang, Carl |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration
by: Xu, Ran, et al.
Published: (2025)
by: Xu, Ran, et al.
Published: (2025)
RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Records
by: Xu, Ran, et al.
Published: (2024)
by: Xu, Ran, et al.
Published: (2024)
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
by: Song, Huatong, et al.
Published: (2025)
by: Song, Huatong, et al.
Published: (2025)
BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers
by: Xu, Ran, et al.
Published: (2024)
by: Xu, Ran, et al.
Published: (2024)
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
by: Jin, Bowen, et al.
Published: (2025)
by: Jin, Bowen, et al.
Published: (2025)
Large Search Model: Redefining Search Stack in the Era of LLMs
by: Wang, Liang, et al.
Published: (2023)
by: Wang, Liang, et al.
Published: (2023)
R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning
by: Song, Huatong, et al.
Published: (2025)
by: Song, Huatong, et al.
Published: (2025)
Unifying Search and Recommendation in LLMs via Gradient Multi-Subspace Tuning
by: Zhao, Jujia, et al.
Published: (2026)
by: Zhao, Jujia, et al.
Published: (2026)
Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning
by: Liang, Zihan, et al.
Published: (2026)
by: Liang, Zihan, et al.
Published: (2026)
Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning
by: Li, Jinzheng, et al.
Published: (2025)
by: Li, Jinzheng, et al.
Published: (2025)
SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis
by: Sun, Shuang, et al.
Published: (2025)
by: Sun, Shuang, et al.
Published: (2025)
SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning
by: Ma, Yufei, et al.
Published: (2026)
by: Ma, Yufei, et al.
Published: (2026)
Retrieval Augmented Conversational Recommendation with Reinforcement Learning
by: Yue, Zhenrui, et al.
Published: (2026)
by: Yue, Zhenrui, et al.
Published: (2026)
RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation
by: Xu, Ran, et al.
Published: (2025)
by: Xu, Ran, et al.
Published: (2025)
Bootstrapping Conditional Retrieval for User-to-Item Recommendations
by: Lin, Hongtao, et al.
Published: (2025)
by: Lin, Hongtao, et al.
Published: (2025)
ReRec: Reasoning-Augmented LLM-based Recommendation Assistant via Reinforcement Fine-tuning
by: Huang, Jiani, et al.
Published: (2026)
by: Huang, Jiani, et al.
Published: (2026)
TongSearch-QR: Reinforced Query Reasoning for Retrieval
by: Qin, Xubo, et al.
Published: (2025)
by: Qin, Xubo, et al.
Published: (2025)
OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework
by: Chen, Ben, et al.
Published: (2026)
by: Chen, Ben, et al.
Published: (2026)
ConvSearch-R1: Enhancing Query Reformulation for Conversational Search with Reasoning via Reinforcement Learning
by: Zhu, Changtai, et al.
Published: (2025)
by: Zhu, Changtai, et al.
Published: (2025)
Efficient Search in Graph Edit Distance: Metric Search Trees vs. Brute Force Verification
by: Guo, Wenqi Marshall, et al.
Published: (2024)
by: Guo, Wenqi Marshall, et al.
Published: (2024)
Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning
by: Mo, Fengran, et al.
Published: (2026)
by: Mo, Fengran, et al.
Published: (2026)
Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs
by: Wang, Ziliang, et al.
Published: (2025)
by: Wang, Ziliang, et al.
Published: (2025)
RAG-R1: Incentivizing the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism
by: Tan, Zhiwen, et al.
Published: (2025)
by: Tan, Zhiwen, et al.
Published: (2025)
SelfRACG: Enabling LLMs to Self-Express and Retrieve for Code Generation
by: Dong, Qian, et al.
Published: (2025)
by: Dong, Qian, et al.
Published: (2025)
Careful Queries, Credible Results: Teaching RAG Models Advanced Web Search Tools with Reinforcement Learning
by: Dai, Yuqin, et al.
Published: (2025)
by: Dai, Yuqin, et al.
Published: (2025)
R3-REC: Reasoning-Driven Recommendation via Retrieval-Augmented LLMs over Multi-Granular Interest Signals
by: Miao, Yuchen, et al.
Published: (2026)
by: Miao, Yuchen, et al.
Published: (2026)
FunReason: Enhancing Large Language Models' Function Calling via Self-Refinement Multiscale Loss and Automated Data Refinement
by: Hao, Bingguang, et al.
Published: (2025)
by: Hao, Bingguang, et al.
Published: (2025)
Automatic Self-supervised Learning for Social Recommendations
by: He, Xin, et al.
Published: (2024)
by: He, Xin, et al.
Published: (2024)
Your Causal Self-Attentive Recommender Hosts a Lonely Neighborhood
by: Wang, Yueqi, et al.
Published: (2024)
by: Wang, Yueqi, et al.
Published: (2024)
SPRec: Self-Play to Debias LLM-based Recommendation
by: Gao, Chongming, et al.
Published: (2024)
by: Gao, Chongming, et al.
Published: (2024)
Factorized Latent Reasoning for LLM-based Recommendation
by: Gao, Tianqi, et al.
Published: (2026)
by: Gao, Tianqi, et al.
Published: (2026)
ScholarSearch: Benchmarking Scholar Searching Ability of LLMs
by: Zhou, Junting, et al.
Published: (2025)
by: Zhou, Junting, et al.
Published: (2025)
MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search
by: Zhang, Sheng, et al.
Published: (2026)
by: Zhang, Sheng, et al.
Published: (2026)
Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models
by: Shi, Wentao, et al.
Published: (2025)
by: Shi, Wentao, et al.
Published: (2025)
DemiNet: Dependency-Aware Multi-Interest Network with Self-Supervised Graph Learning for Click-Through Rate Prediction
by: Wang, Yule, et al.
Published: (2021)
by: Wang, Yule, et al.
Published: (2021)
Bootstrap Your Own Context Length
by: Wang, Liang, et al.
Published: (2024)
by: Wang, Liang, et al.
Published: (2024)
IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning
by: Liang, Zihan, et al.
Published: (2026)
by: Liang, Zihan, et al.
Published: (2026)
Reinforced Preference Optimization for Reasoning-Augmented Recommendations
by: Gao, Jingtong, et al.
Published: (2026)
by: Gao, Jingtong, et al.
Published: (2026)
Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation
by: Wang, Shijie, et al.
Published: (2025)
by: Wang, Shijie, et al.
Published: (2025)
From Reasoning LLMs to BERT: A Two-Stage Distillation Framework for Search Relevance
by: Xia, Runze, et al.
Published: (2025)
by: Xia, Runze, et al.
Published: (2025)
Similar Items
-
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration
by: Xu, Ran, et al.
Published: (2025) -
RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Records
by: Xu, Ran, et al.
Published: (2024) -
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
by: Song, Huatong, et al.
Published: (2025) -
BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers
by: Xu, Ran, et al.
Published: (2024) -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
by: Jin, Bowen, et al.
Published: (2025)