:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Shiyu, Tang, Yang, Wang, Yifan, Li, Peiming, Chen, Xi
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language
Acceso en línea:	https://arxiv.org/abs/2510.00568
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning
por: Wang, Yifan, et al.
Publicado: (2026)

SE-Search: Self-Evolving Search Agent via Memory and Dense Reward
por: Li, Jian, et al.
Publicado: (2026)

Finetune Once: Decoupling General & Domain Learning with Dynamic Boosted Annealing
por: Tang, Yang, et al.
Publicado: (2025)

Instructive Dialogue Summarization with Query Aggregations
por: Wang, Bin, et al.
Publicado: (2023)

Conan-embedding: General Text Embedding with More and Better Negative Samples
por: Li, Shiyu, et al.
Publicado: (2024)

ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search
por: Zhang, Dan, et al.
Publicado: (2024)

Multi-Agent Consensus Seeking via Large Language Models
por: Chen, Huaben, et al.
Publicado: (2023)

ExpSeek: Self-Triggered Experience Seeking for Web Agents
por: Zhang, Wenyuan, et al.
Publicado: (2026)

InfoMosaic-Bench: Evaluating Multi-Source Information Seeking in Tool-Augmented Agents
por: Du, Yaxin, et al.
Publicado: (2025)

WideSearch: Benchmarking Agentic Broad Info-Seeking
por: Wong, Ryan, et al.
Publicado: (2025)

Retrieval, Reward, and Training Protocols: What Matters in Training Search Agents?
por: Zhao, Yibo, et al.
Publicado: (2026)

Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extraction
por: Li, Guozheng, et al.
Publicado: (2024)

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
por: Kim, Taehyeon, et al.
Publicado: (2023)

Conan-Embedding-v2: Training an LLM from Scratch for Text Embeddings
por: Li, Shiyu, et al.
Publicado: (2025)

SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation
por: Hu, Minda, et al.
Publicado: (2024)

InfoAgent: Advancing Autonomous Information-Seeking Agents
por: Zhang, Gongrui, et al.
Publicado: (2025)

EvolveSearch: An Iterative Self-Evolving Search Agent
por: Zhang, Dingchu, et al.
Publicado: (2025)

RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
por: Wang, Peisong, et al.
Publicado: (2025)

ReFINE: A Reward-Based Framework for Interpretable and Nuanced Evaluation of Radiology Report Generation
por: Liu, Yunyi, et al.
Publicado: (2024)

Sparse Rewards Can Self-Train Dialogue Agents
por: Lattimer, Barrett Martin, et al.
Publicado: (2024)

Triviality Corrected Endogenous Reward
por: Wang, Xinda, et al.
Publicado: (2026)

Re-ReST: Reflection-Reinforced Self-Training for Language Agents
por: Dou, Zi-Yi, et al.
Publicado: (2024)

AgentCollab: A Self-Evaluation-Driven Collaboration Paradigm for Efficient LLM Agents
por: Gao, Wenbo, et al.
Publicado: (2026)

ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoning
por: Wu, Juncheng, et al.
Publicado: (2026)

SmartSnap: Proactive Evidence Seeking for Self-Verifying Agents
por: Cai, Shaofei, et al.
Publicado: (2025)

Beyond Retrieval-Ranking: A Multi-Agent Cognitive Decision Framework for E-Commerce Search
por: Zhai, Zhouwei, et al.
Publicado: (2025)

ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding
por: Sun, Zhongxiang, et al.
Publicado: (2025)

Think&Cite: Improving Attributed Text Generation with Self-Guided Tree Search and Progress Reward Modeling
por: Li, Junyi, et al.
Publicado: (2024)

Chaining the Evidence: Robust Reinforcement Learning for Deep Search Agents with Citation-Aware Rubric Rewards
por: Zhang, Jiajie, et al.
Publicado: (2026)

A Comprehensive Graph Framework for Question Answering with Mode-Seeking Preference Alignment
por: Tang, Quanwei, et al.
Publicado: (2025)

Reward Auditor: Inference on Reward Modeling Suitability in Real-World Perturbed Scenarios
por: Zang, Jianxiang, et al.
Publicado: (2025)

The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement
por: Wang, Xiaobo, et al.
Publicado: (2026)

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
por: Chen, Mingyang, et al.
Publicado: (2025)

Aligning Deep Implicit Preferences by Learning to Reason Defensively
por: Li, Peiming, et al.
Publicado: (2025)

Self-Correction Makes LLMs Better Parsers
por: Zhang, Ziyan, et al.
Publicado: (2025)

Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing
por: Guo, Peiming, et al.
Publicado: (2025)

DeepWideSearch: Benchmarking Depth and Width in Agentic Information Seeking
por: Lan, Tian, et al.
Publicado: (2025)

URPO: A Unified Reward & Policy Optimization Framework for Large Language Models
por: Lu, Songshuo, et al.
Publicado: (2025)

VL-RewardBench: A Challenging Benchmark for Vision-Language Generative Reward Models
por: Li, Lei, et al.
Publicado: (2024)

ARIA: Training Language Agents with Intention-Driven Reward Aggregation
por: Yang, Ruihan, et al.
Publicado: (2025)