:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Hongming, Liu, Yang, Huang, Chao
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2602.17465
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revisiting a Pain in the Neck: A Semantic Reasoning Benchmark for Language Models
by: Liu, Yang, et al.
Published: (2026)

Revisiting a Pain in the Neck: Semantic Phrase Processing Benchmark for Language Models
by: Liu, Yang, et al.
Published: (2024)

Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language Models
by: Zhang, Zhisong, et al.
Published: (2024)

Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
by: Chen, Xin, et al.
Published: (2026)

Entropy-Based Decoding for Retrieval-Augmented Large Language Models
by: Qiu, Zexuan, et al.
Published: (2024)

Data Selection via Optimal Control for Language Models
by: Gu, Yuxian, et al.
Published: (2024)

Enhancing Large Language Models with Domain-Specific Knowledge: The Case in Topological Materials
by: Xu, HuangChao, et al.
Published: (2024)

On-the-fly Denoising for Data Augmentation in Natural Language Understanding
by: Fang, Tianqing, et al.
Published: (2022)

InstructDiff: Domain-Adaptive Data Selection via Differential Entropy for Efficient LLM Fine-Tuning
by: Su, Junyou, et al.
Published: (2026)

InComeS: Integrating Compression and Selection Mechanisms into LLMs for Efficient Model Editing
by: Li, Shuaiyi, et al.
Published: (2025)

Cost-efficient Crowdsourcing for Span-based Sequence Labeling: Worker Selection and Data Augmentation
by: Wang, Yujie, et al.
Published: (2023)

SocREval: Large Language Models with the Socratic Method for Reference-Free Reasoning Evaluation
by: He, Hangfeng, et al.
Published: (2023)

Entropy-Based Block Pruning for Efficient Large Language Models
by: Yang, Liangwei, et al.
Published: (2025)

ZPD Detector: Data Selection via Capability-Difficulty Alignment for Large Language Models
by: Yang, Bo, et al.
Published: (2026)

Structural-Entropy-Based Sample Selection for Efficient and Effective Learning
by: Xie, Tianchi, et al.
Published: (2024)

Entropy-Guided Token Dropout: Training Autoregressive Language Models with Limited Domain Data
by: Wang, Jiapeng, et al.
Published: (2025)

Entropy in Large Language Models
by: Scharringhausen, Marco
Published: (2026)

Take the essence and discard the dross: A Rethinking on Data Selection for Fine-Tuning Large Language Models
by: Liu, Ziche, et al.
Published: (2024)

CLOMO: Counterfactual Logical Modification with Large Language Models
by: Huang, Yinya, et al.
Published: (2023)

A Survey on Data Selection for Language Models
by: Albalak, Alon, et al.
Published: (2024)

Thrust: Adaptively Propels Large Language Models with External Knowledge
by: Zhao, Xinran, et al.
Published: (2023)

DavIR: Data Selection via Implicit Reward for Large Language Models
by: Zhou, Haotian, et al.
Published: (2023)

Abstraction-of-Thought Makes Language Models Better Reasoners
by: Hong, Ruixin, et al.
Published: (2024)

Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models
by: Lee, Joseph, et al.
Published: (2024)

DaMoC: Efficiently Selecting the Optimal Large Language Model for Fine-tuning Domain Tasks Based on Data and Model Compression
by: Huang, Wei, et al.
Published: (2025)

Investigating the Impact of Data Selection Strategies on Language Model Performance
by: Gu, Jiayao, et al.
Published: (2025)

Entropy2Vec: Crosslingual Language Modeling Entropy as End-to-End Learnable Language Representations
by: Irawan, Patrick Amadeus, et al.
Published: (2025)

Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data Selection
by: Chen, Ruibo, et al.
Published: (2024)

M-GRPO: Stabilizing Self-Supervised Reinforcement Learning for Large Language Models with Momentum-Anchored Policy Optimization
by: Bai, Bizhe, et al.
Published: (2025)

OPUS: Towards Efficient and Principled Data Selection in Large Language Model Pre-training in Every Iteration
by: Wang, Shaobo, et al.
Published: (2026)

EDT: Improving Large Language Models' Generation by Entropy-based Dynamic Temperature Sampling
by: Zhang, Shimao, et al.
Published: (2024)

Selective Annotation via Data Allocation: These Data Should Be Triaged to Experts for Annotation Rather Than the Model
by: Huang, Chen, et al.
Published: (2024)

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?
by: Wang, Jingyuan, et al.
Published: (2025)

Conceptual and Unbiased Reasoning in Language Models
by: Zhou, Ben, et al.
Published: (2024)

Enhancing Large Language Model Performance with Gradient-Based Parameter Selection
by: Li, Haoling, et al.
Published: (2024)

A Hierarchical Framework for Measuring Scientific Paper Innovation via Large Language Models
by: Tan, Hongming, et al.
Published: (2025)

Entropy-Tree: Tree-Based Decoding with Entropy-Guided Exploration
by: Wei, Longxuan, et al.
Published: (2026)

Improved Techniques for Optimization-Based Jailbreaking on Large Language Models
by: Jia, Xiaojun, et al.
Published: (2024)

Influential Language Data Selection via Gradient Trajectory Pursuit
by: Deng, Zhiwei, et al.
Published: (2024)

Efficient Beam Search for Large Language Models Using Trie-Based Decoding
by: Chan, Brian J, et al.
Published: (2025)