:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Muhebwa, Aggrey, Osman, Khalid K.
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2505.19511
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Kuramoto-FedAvg: Using Synchronization Dynamics to Improve Federated Learning Optimization under Statistical Heterogeneity
by: Muhebwa, Aggrey, et al.
Published: (2025)

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

Compact Example-Based Explanations for Language Models
by: Schoenegger, Loris, et al.
Published: (2026)

LANTERN: Scalable Distillation of Large Language Models for Job-Person Fit and Explanation
by: Fu, Zhoutong, et al.
Published: (2025)

Distilling Text Style Transfer With Self-Explanation From LLMs
by: Zhang, Chiyu, et al.
Published: (2024)

Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models
by: Yang, Junjie, et al.
Published: (2025)

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

Distilling LLMs' Decomposition Abilities into Compact Language Models
by: Tarasov, Denis, et al.
Published: (2024)

Compact Language Models via Pruning and Knowledge Distillation
by: Muralidharan, Saurav, et al.
Published: (2024)

Narrating Causal Graphs with Large Language Models
by: Phatak, Atharva, et al.
Published: (2024)

Distilling Empathy from Large Language Models
by: Xie, Henry J., et al.
Published: (2025)

Quantification of Large Language Model Distillation
by: Lee, Sunbowen, et al.
Published: (2025)

Evaluating the Reliability of Self-Explanations in Large Language Models
by: Randl, Korbinian, et al.
Published: (2024)

Large Language Models as Evaluators for Recommendation Explanations
by: Zhang, Xiaoyu, et al.
Published: (2024)

ProtStructQA: A Denotation Threshold in Protein Structural Reasoning
by: Mandiga, Aravind, et al.
Published: (2026)

How Interpretable are Reasoning Explanations from Prompting Large Language Models?
by: Yeo, Wei Jie, et al.
Published: (2024)

Exploring and Enhancing the Transfer of Distribution in Knowledge Distillation for Autoregressive Language Models
by: Rao, Jun, et al.
Published: (2024)

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations
by: Atakishiyev, Shahin, et al.
Published: (2025)

KoRe: Compact Knowledge Representations for Large Language Models
by: Cavicchini, Davide, et al.
Published: (2026)

Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models
by: Agarwal, Chirag, et al.
Published: (2024)

On the Reliability of Large Language Models for Causal Discovery
by: Feng, Tao, et al.
Published: (2024)

Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality
by: Ying, Lance, et al.
Published: (2025)

Investigating Training and Generalization in Faithful Self-Explanations of Large Language Models
by: Doi, Tomoki, et al.
Published: (2025)

Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues
by: Fichtel, Leandra, et al.
Published: (2025)

PromptExp: Multi-granularity Prompt Explanation of Large Language Models
by: Dong, Ximing, et al.
Published: (2024)

Natural Language Counterfactual Explanations for Graphs Using Large Language Models
by: Giorgi, Flavio, et al.
Published: (2024)

Knowledge Distillation of Black-Box Large Language Models
by: Chen, Hongzhan, et al.
Published: (2024)

Distilling Rule-based Knowledge into Large Language Models
by: Yang, Wenkai, et al.
Published: (2023)

Direct Preference Knowledge Distillation for Large Language Models
by: Li, Yixing, et al.
Published: (2024)

A Survey on Knowledge Distillation of Large Language Models
by: Xu, Xiaohan, et al.
Published: (2024)

Transfer Learning for Finetuning Large Language Models
by: Strangmann, Tobias, et al.
Published: (2024)

The Role of Language Models in Modern Healthcare: A Comprehensive Review
by: Khalid, Amna, et al.
Published: (2024)

Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
by: Zhao, Siyan, et al.
Published: (2026)

Causality for Large Language Models
by: Wu, Anpeng, et al.
Published: (2024)

Inference to the Best Explanation in Large Language Models
by: Dalal, Dhairya, et al.
Published: (2024)

Explanations of Large Language Models Explain Language Representations in the Brain
by: Rahimi, Maryam, et al.
Published: (2025)

Distilling Fine-grained Sentiment Understanding from Large Language Models
by: Zhang, Yice, et al.
Published: (2024)

Distilling Reasoning Ability from Large Language Models with Adaptive Thinking
by: Chen, Xiaoshu, et al.
Published: (2024)

A Causal Explainable Guardrails for Large Language Models
by: Chu, Zhixuan, et al.
Published: (2024)

FakeGPT: Fake News Generation, Explanation and Detection of Large Language Models
by: Huang, Yue, et al.
Published: (2023)