Copertina

ReAD: Reinforcement-Guided Capability Distillation for Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cheng, Xueqi, Zhou, Xugui, Derr, Tyler, Dong, Yushun
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

SOMA: Efficient Multi-turn LLM Serving via Small Language Model
di: Cheng, Xueqi, et al.
Pubblicazione: (2026)

LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer?
di: Cheng, Xueqi, et al.
Pubblicazione: (2026)

Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest
di: Davoudi, Ramtin, et al.
Pubblicazione: (2026)

Think Before You Speak: Cultivating Communication Skills of Large Language Models via Inner Monologue
di: Zhou, Junkai, et al.
Pubblicazione: (2023)

Knowledge Graph-Enhanced Large Language Models via Path Selection
di: Liu, Haochen, et al.
Pubblicazione: (2024)

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey
di: Ni, Bo, et al.
Pubblicazione: (2025)

Towards Trustworthy Knowledge Graph Reasoning: An Uncertainty Aware Perspective
di: Ni, Bo, et al.
Pubblicazione: (2024)

Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning
di: Hu, Bokai, et al.
Pubblicazione: (2024)

ELAD: Explanation-Guided Large Language Models Active Distillation
di: Zhang, Yifei, et al.
Pubblicazione: (2024)

Distilling Mathematical Reasoning Capabilities into Small Language Models
di: Zhu, Xunyu, et al.
Pubblicazione: (2024)

KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models
di: Zheng, Zaiyi, et al.
Pubblicazione: (2025)

From Correction to Mastery: Reinforced Distillation of Large Language Model Agents
di: Lyu, Yuanjie, et al.
Pubblicazione: (2025)

Evaluating Implicit Bias in Large Language Models by Attacking From a Psychometric Perspective
di: Wen, Yuchen, et al.
Pubblicazione: (2024)

MiniLLM: On-Policy Distillation of Large Language Models
di: Gu, Yuxian, et al.
Pubblicazione: (2023)

MISLEADER: Defending against Model Extraction with Ensembles of Distilled Models
di: Cheng, Xueqi, et al.
Pubblicazione: (2025)

Black-Box On-Policy Distillation of Large Language Models
di: Ye, Tianzhu, et al.
Pubblicazione: (2025)

AD-GPT: Large Language Models in Alzheimer's Disease
di: Liu, Ziyu, et al.
Pubblicazione: (2025)

Reinforcement Learning vs. Distillation: Understanding Accuracy and Capability in LLM Reasoning
di: Kim, Minwu, et al.
Pubblicazione: (2025)

AD-LLM: Benchmarking Large Language Models for Anomaly Detection
di: Yang, Tiankai, et al.
Pubblicazione: (2024)

UNLEARN Efficient Removal of Knowledge in Large Language Models
di: Lizzo, Tyler, et al.
Pubblicazione: (2024)

Large Language Model Sourcing: A Survey
di: Pang, Liang, et al.
Pubblicazione: (2025)

Improving Mathematical Reasoning Capabilities of Small Language Models via Feedback-Driven Distillation
di: Zhu, Xunyu, et al.
Pubblicazione: (2024)

StruEdit: Structured Outputs Enable the Fast and Accurate Knowledge Editing for Large Language Models
di: Bi, Baolong, et al.
Pubblicazione: (2024)

Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models
di: Dong, Guanting, et al.
Pubblicazione: (2024)

Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation
di: Xu, Shicheng, et al.
Pubblicazione: (2024)

UNDIAL: Self-Distillation with Adjusted Logits for Robust Unlearning in Large Language Models
di: Dong, Yijiang River, et al.
Pubblicazione: (2024)

Chunk-Distilled Language Modeling
di: Li, Yanhong, et al.
Pubblicazione: (2024)

Structured Agent Distillation for Large Language Model
di: Liu, Jun, et al.
Pubblicazione: (2025)

Reasoning Capabilities of Large Language Models on Dynamic Tasks
di: Wong, Annie, et al.
Pubblicazione: (2025)

Evaluating Consistency and Reasoning Capabilities of Large Language Models
di: Saxena, Yash, et al.
Pubblicazione: (2024)

Do Large Language Models Know What They Are Capable Of?
di: Barkan, Casey O., et al.
Pubblicazione: (2025)

On the Use of Large Language Models to Generate Capability Ontologies
di: da Silva, Luis Miguel Vieira, et al.
Pubblicazione: (2024)

Enhancing the Traditional Chinese Medicine Capabilities of Large Language Model through Reinforcement Learning from AI Feedback
di: Yu, Song, et al.
Pubblicazione: (2024)

Cross-Modal Safety Mechanism Transfer in Large Vision-Language Models
di: Xu, Shicheng, et al.
Pubblicazione: (2024)

Measuring and Benchmarking Large Language Models' Capabilities to Generate Persuasive Language
di: Pauli, Amalie Brogaard, et al.
Pubblicazione: (2024)

Preservation of Language Understanding Capabilities in Speech-aware Large Language Models
di: Kubis, Marek, et al.
Pubblicazione: (2025)

BiLD: Bi-directional Logits Difference Loss for Large Language Model Distillation
di: Li, Minchong, et al.
Pubblicazione: (2024)

Enhancing Reasoning Capabilities in SLMs with Reward Guided Dataset Distillation
di: Padarha, Shreyansh
Pubblicazione: (2025)

In Context Learning and Reasoning for Symbolic Regression with Large Language Models
di: Sharlin, Samiha, et al.
Pubblicazione: (2024)

QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models
di: Wang, Wei, et al.
Pubblicazione: (2024)