Cover Image

Exploring Information Processing in Large Language Models: Insights from Information Bottleneck Theory

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Zhou, Qi, Zhengyu, Ren, Zhaochun, Jia, Zhikai, Sun, Haizhou, Zhu, Xiaofei, Liao, Xiangwen
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An Iterative Associative Memory Model for Empathetic Response Generation
by: Yang, Zhou, et al.
Published: (2024)

Fine-Grained Emotion Recognition via In-Context Learning
by: Ren, Zhaochun, et al.
Published: (2025)

E-ICL: Enhancing Fine-Grained Emotion Recognition through the Lens of Prototype Theory
by: Ren, Zhaochun, et al.
Published: (2024)

Exploiting Emotion-Semantic Correlations for Empathetic Response Generation
by: Yang, Zhou, et al.
Published: (2024)

Enhancing Empathetic Response Generation by Augmenting LLMs with Small-scale Empathetic Models
by: Yang, Zhou, et al.
Published: (2024)

Cognitive Biases in Large Language Models for News Recommendation
by: Lyu, Yougang, et al.
Published: (2024)

ChatUIE: Exploring Chat-based Unified Information Extraction using Large Language Models
by: Xu, Jun, et al.
Published: (2024)

QUITO-X: A New Perspective on Context Compression from the Information Bottleneck Theory
by: Wang, Yihang, et al.
Published: (2024)

CTSM: Combining Trait and State Emotions for Empathetic Response Model
by: Yufeng, Wang, et al.
Published: (2024)

Retrieval Models Aren't Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models
by: Shi, Zhengliang, et al.
Published: (2025)

Self-Supervised Position Debiasing for Large Language Models
by: Liu, Zhongkun, et al.
Published: (2024)

KnowTuning: Knowledge-aware Fine-tuning for Large Language Models
by: Lyu, Yougang, et al.
Published: (2024)

SeSE: Black-Box Uncertainty Quantification for Large Language Models Based on Structural Information Theory
by: Zhao, Xingtao, et al.
Published: (2025)

Enhancing RAG Efficiency with Adaptive Context Compression
by: Guo, Shuyu, et al.
Published: (2025)

Do Large Language Models Mirror Cognitive Language Processing?
by: Ren, Yuqi, et al.
Published: (2024)

LEGO Co-builder: Exploring Fine-Grained Vision-Language Modeling for Multimodal LEGO Assembly Assistants
by: Huang, Haochen, et al.
Published: (2025)

Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models
by: Zhou, Yue, et al.
Published: (2024)

Red Teaming Language Models for Processing Contradictory Dialogues
by: Wen, Xiaofei, et al.
Published: (2024)

An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation
by: Zhu, Kun, et al.
Published: (2024)

Protecting Your LLMs with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)

Information Gain-Guided Causal Intervention for Autonomous Debiasing Large Language Models
by: Sun, Zhouhao, et al.
Published: (2025)

Sparsity Induction for Accurate Post-Training Pruning of Large Language Models
by: Jiang, Minhao, et al.
Published: (2026)

Multi-Scale Manifold Alignment for Interpreting Large Language Models: A Unified Information-Geometric Framework
by: Zhang, Yukun, et al.
Published: (2025)

MALM: A Multi-Information Adapter for Large Language Models to Mitigate Hallucination
by: Jia, Ao, et al.
Published: (2025)

Emergent Hierarchical Structure in Large Language Models: An Information-Theoretic Framework for Multi-Scale Representation
by: Zhang, Yukin, et al.
Published: (2025)

Large Language Models Explore by Latent Distilling
by: Zeng, Yuanhao, et al.
Published: (2026)

A Universal Prompting Strategy for Extracting Process Model Information from Natural Language Text using Large Language Models
by: Neuberger, Julian, et al.
Published: (2024)

LLM Inference Unveiled: Survey and Roofline Model Insights
by: Yuan, Zhihang, et al.
Published: (2024)

Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models
by: Liu, Ji, et al.
Published: (2024)

Exploring the Compositional Deficiency of Large Language Models in Mathematical Reasoning
by: Zhao, Jun, et al.
Published: (2024)

Disentangling Knowledge Representations for Large Language Model Editing
by: Zhang, Mengqi, et al.
Published: (2025)

Evaluating the Performance of Large Language Models on GAOKAO Benchmark
by: Zhang, Xiaotian, et al.
Published: (2023)

GraphArena: Evaluating and Exploring Large Language Models on Graph Computation
by: Tang, Jianheng, et al.
Published: (2024)

Exploring and Evaluating Multimodal Knowledge Reasoning Consistency of Multimodal Large Language Models
by: Jia, Boyu, et al.
Published: (2025)

Training-Free Bayesianization for Low-Rank Adapters of Large Language Models
by: Shi, Haizhou, et al.
Published: (2024)

Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck
by: Zhang, Hongbin, et al.
Published: (2026)

Teaching Language Models To Gather Information Proactively
by: Huang, Tenghao, et al.
Published: (2025)

LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?
by: Zou, Kaijian, et al.
Published: (2025)

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models
by: Zheng, Congmin, et al.
Published: (2025)

BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models
by: Wang, Yibin, et al.
Published: (2024)