Cover Image

Probing to Refine: Reinforcement Distillation of LLMs via Explanatory Inversion

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tan, Zhen, Zhao, Chengshuai, Wang, Song, Li, Jundong, Chen, Tianlong, Liu, Huan
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Are We Merely Justifying Results ex Post Facto? Quantifying Explanatory Inversion in Post-Hoc Model Explanations
by: Tan, Zhen, et al.
Published: (2025)

GraphRCG: Self-Conditioned Graph Generation
by: Wang, Song, et al.
Published: (2024)

DOGe: Defensive Output Generation for LLM Protection Against Knowledge Distillation
by: Li, Pingzhi, et al.
Published: (2025)

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
by: Zhao, Chengshuai, et al.
Published: (2025)

Can GRPO Help LLMs Transcend Their Pretraining Origin?
by: Ni, Kangqi, et al.
Published: (2025)

Leave It to the Experts: Detecting Knowledge Distillation via MoE Expert Signatures
by: Li, Pingzhi, et al.
Published: (2025)

Efficient Prompt Optimization Through the Lens of Best Arm Identification
by: Shi, Chengshuai, et al.
Published: (2024)

DLO: Dynamic Layer Operation for Efficient Vertical Scaling of LLMs
by: Tan, Zhen, et al.
Published: (2024)

The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative
by: Tan, Zhen, et al.
Published: (2024)

To See is Not to Learn: Protecting Multimodal Data from Unauthorized Fine-Tuning of Large Vision-Language Model
by: Zhao, Chengshuai, et al.
Published: (2026)

Finding the Cracks: Improving LLMs Reasoning with Paraphrastic Probing and Consistency Verification
by: Shi, Weili, et al.
Published: (2026)

Contextualization Distillation from Large Language Model for Knowledge Graph Completion
by: Li, Dawei, et al.
Published: (2024)

QuantMoE-Bench: Examining Post-Training Quantization for Mixture-of-Experts
by: Li, Pingzhi, et al.
Published: (2024)

KDRL: Post-Training Reasoning LLMs via Unified Knowledge Distillation and Reinforcement Learning
by: Xu, Hongling, et al.
Published: (2025)

SCALE: Towards Collaborative Content Analysis in Social Science with Large Language Model Agents and Human Intervention
by: Zhao, Chengshuai, et al.
Published: (2025)

Causality Guided Representation Learning for Cross-Style Hate Speech Detection
by: Zhao, Chengshuai, et al.
Published: (2025)

Learning to Refine: Self-Refinement of Parallel Reasoning in LLMs
by: Wang, Qibin, et al.
Published: (2025)

Are Today's LLMs Ready to Explain Well-Being Concepts?
by: Jiang, Bohan, et al.
Published: (2025)

Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
by: Le, Qi, et al.
Published: (2025)

Explanatory Summarization with Discourse-Driven Planning
by: Liu, Dongqi, et al.
Published: (2025)

Catching Chameleons: Detecting Evolving Disinformation Generated using Large Language Models
by: Jiang, Bohan, et al.
Published: (2024)

The Quest for Efficient Reasoning: A Data-Centric Benchmark to CoT Distillation
by: Zhang, Ruichen, et al.
Published: (2025)

Semantic Refinement with LLMs for Graph Representations
by: Thapaliya, Safal, et al.
Published: (2025)

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning
by: Qian, Cheng, et al.
Published: (2025)

"Glue pizza and eat rocks" -- Exploiting Vulnerabilities in Retrieval-Augmented Generative Models
by: Tan, Zhen, et al.
Published: (2024)

Evolutionary Guided Decoding: Iterative Value Refinement for LLMs
by: Liu, Zhenhua, et al.
Published: (2025)

DeferMem: Query-Time Evidence Distillation via Reinforcement Learning for Long-Term Memory QA
by: Yin, Jianing, et al.
Published: (2026)

True Knowledge Comes from Practice: Aligning LLMs with Embodied Environments via Reinforcement Learning
by: Tan, Weihao, et al.
Published: (2024)

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory
by: Dong, Songwei, et al.
Published: (2026)

Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning
by: Shi, Chengshuai, et al.
Published: (2026)

DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
by: DeepSeek-AI, et al.
Published: (2025)

Beyond Redundancy: Diverse and Specialized Multi-Expert Sparse Autoencoder
by: Xu, Zhen, et al.
Published: (2025)

Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement
by: Xiong, Weimin, et al.
Published: (2024)

Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
by: Xu, Wanghan, et al.
Published: (2025)

Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
by: Wang, Song, et al.
Published: (2025)

DRAG: Distilling RAG for SLMs from LLMs to Transfer Knowledge and Mitigate Hallucination via Evidence and Graph-based Distillation
by: Chen, Jennifer, et al.
Published: (2025)

Prediction is not Explanation: Revisiting the Explanatory Capacity of Mapping Embeddings
by: Herasimchyk, Hanna, et al.
Published: (2025)

GTBench: Uncovering the Strategic Reasoning Limitations of LLMs via Game-Theoretic Evaluations
by: Duan, Jinhao, et al.
Published: (2024)

RLFR: Extending Reinforcement Learning for LLMs with Flow Environment
by: Zhang, Jinghao, et al.
Published: (2025)

UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Making
by: Duan, Jinhao, et al.
Published: (2025)