:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Shi, Boyu, Jiang, YiCheng, Liu, Chang, Wang, Qiufeng, Yang, Xu, Geng, Xin
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2605.07783
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

XPERT: Expert Knowledge Transfer for Effective Training of Language Models
by: Liu, Chang, et al.
Published: (2026)

Learngene Search Across Multiple Datasets for Building Variable-Sized Models
by: Shi, Boyu, et al.
Published: (2026)

Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions
by: Shi, Boyu, et al.
Published: (2026)

Thinking-Free Policy Initialization Makes Distilled Reasoning Models More Effective and Efficient Reasoners
by: Xu, Xin, et al.
Published: (2025)

Reionization History and Neutrino Mass
by: Dai, YiCheng, et al.
Published: (2026)

Constraint on Neutrino Statistics from Cosmological Data
by: Dai, YiCheng, et al.
Published: (2025)

SOD: Step-wise On-policy Distillation for Small Language Model Agents
by: Zhong, Qiyong, et al.
Published: (2026)

Cross-Cultural Expert-Level Art Critique Evaluation with Vision-Language Models
by: Yu, Haorui, et al.
Published: (2026)

Effectiveness of Chain-of-Thought in Distilling Reasoning Capability from Large Language Models
by: Do, Cong-Thanh, et al.
Published: (2025)

Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step
by: Li, Liunian Harold, et al.
Published: (2023)

An Analysis for Reasoning Bias of Language Models with Small Initialization
by: Yao, Junjie, et al.
Published: (2025)

Seeing Symbols, Missing Cultures: Probing Vision-Language Models' Reasoning on Fire Imagery and Cultural Meaning
by: Yu, Haorui, et al.
Published: (2025)

Balanced Actor Initialization: Stable RLHF Training of Distillation-Based Reasoning Models
by: Zheng, Chen, et al.
Published: (2025)

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

SLMRec: Distilling Large Language Models into Small for Sequential Recommendation
by: Xu, Wujiang, et al.
Published: (2024)

InfiR : Crafting Effective Small Language Models and Multimodal Small Language Models in Reasoning
by: Xie, Congkai, et al.
Published: (2025)

Adam: Dense Retrieval Distillation with Adaptive Dark Examples
by: Tao, Chongyang, et al.
Published: (2022)

Learning to Rank Chain-of-Thought: Using a Small Model
by: Jiang, Eric Hanchen, et al.
Published: (2025)

Progressively Label Enhancement for Large Language Model Alignment
by: Liu, Biao, et al.
Published: (2024)

CANDLE: Iterative Conceptualization and Instantiation Distillation from Large Language Models for Commonsense Reasoning
by: Wang, Weiqi, et al.
Published: (2024)

Preference Orchestrator: Prompt-Aware Multi-Objective Alignment for Large Language Models
by: Liu, Biao, et al.
Published: (2025)

Learning to Maximize Mutual Information for Chain-of-Thought Distillation
by: Chen, Xin, et al.
Published: (2024)

Self and Cross-Model Distillation for LLMs: Effective Methods for Refusal Pattern Alignment
by: Li, Jie, et al.
Published: (2024)

BOLT: Bootstrap Long Chain-of-Thought in Language Models without Distillation
by: Pang, Bo, et al.
Published: (2025)

Enhancing Generalization in Chain of Thought Reasoning for Smaller Models
by: Yin, Maxwell J., et al.
Published: (2025)

Capturing Nuanced Preferences: Preference-Aligned Distillation for Small Language Models
by: Gu, Yanggan, et al.
Published: (2025)

Neural-Symbolic Collaborative Distillation: Advancing Small Language Models for Complex Reasoning Tasks
by: Liao, Huanxuan, et al.
Published: (2024)

Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought
by: Lee, Jooyoung, et al.
Published: (2024)

Advantage-Guided Distillation for Preference Alignment in Small Language Models
by: Gao, Shiping, et al.
Published: (2025)

VULCA-Bench: A Multicultural Vision-Language Benchmark for Evaluating Cultural Understanding
by: Yu, Haorui, et al.
Published: (2026)

ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting
by: Cheng, Xiaoxue, et al.
Published: (2024)

Scaling Law for Language Models Training Considering Batch Size
by: Shuai, Xian, et al.
Published: (2024)

MeTA-LoRA: Data-Efficient Multi-Task Fine-Tuning for Large Language Models
by: Cheng, Bo, et al.
Published: (2025)

Reasoning-preserved Efficient Distillation of Large Language Models via Activation-aware Initialization
by: He, Junlin, et al.
Published: (2026)

ROSD: Reflective On-Policy Self-Distillation for Language Model Reasoning across Domains
by: Zhao, Ziqi, et al.
Published: (2026)

EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models
by: Wang, Chengyu, et al.
Published: (2025)

Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models
by: Xia, Shi-Yu, et al.
Published: (2024)

FedCoT: Federated Chain-of-Thought Distillation for Large Language Models
by: Fan, Tao, et al.
Published: (2024)

Small Language Models as Effective Guides for Large Language Models in Chinese Relation Extraction
by: Tang, Xuemei, et al.
Published: (2024)

A Structured Framework for Evaluating and Enhancing Interpretive Capabilities of Multimodal LLMs in Culturally Situated Tasks
by: Yu, Haorui, et al.
Published: (2025)