Copertina

Internal narratives parameterise affective states

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Onysk, Jakub, Huys, Quentin J. M.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Mastering Board Games by External and Internal Planning with Language Models
di: Schultz, John, et al.
Pubblicazione: (2024)

Pre-training Limited Memory Language Models with Internal and External Knowledge
di: Zhao, Linxi, et al.
Pubblicazione: (2025)

Co-Evolution of Policy and Internal Reward for Language Agents
di: Wang, Xinyu, et al.
Pubblicazione: (2026)

SE-Bench: Benchmarking Self-Evolution with Knowledge Internalization
di: Yuan, Jiarui, et al.
Pubblicazione: (2026)

Scaling Fine-Grained MoE Beyond 50B Parameters: Empirical Evaluation and Practical Insights
di: Krajewski, Jakub, et al.
Pubblicazione: (2025)

Interpretable Predictability-Based AI Text Detection: A Replication Study
di: Skurla, Adam, et al.
Pubblicazione: (2026)

Cross-lingual Named Entity Corpus for Slavic Languages
di: Piskorski, Jakub, et al.
Pubblicazione: (2024)

Superscopes: Amplifying Internal Feature Representations for Language Model Interpretation
di: Jacobi, Jonathan, et al.
Pubblicazione: (2025)

Internal Planning in Language Models: Characterizing Horizon and Branch Awareness
di: Ustaomeroglu, Muhammed, et al.
Pubblicazione: (2025)

SelfReflect: Can LLMs Communicate Their Internal Answer Distribution?
di: Kirchhof, Michael, et al.
Pubblicazione: (2025)

Internalizing LLM Reasoning via Discovery and Replay of Latent Actions
di: Shi, Zhenning, et al.
Pubblicazione: (2026)

MICE for CATs: Model-Internal Confidence Estimation for Calibrating Agents with Tools
di: Subramani, Nishant, et al.
Pubblicazione: (2025)

Bridging Internal Probability and Self-Consistency for Effective and Efficient LLM Reasoning
di: Zhou, Zhi, et al.
Pubblicazione: (2025)

Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation
di: Qi, Jirui, et al.
Pubblicazione: (2024)

Discourse vs emissions: Analysis of corporate narratives, symbolic practices, and mimicry through LLMs
di: Hassani, Bertrand Kian, et al.
Pubblicazione: (2025)

Affinity and Diversity: A Unified Metric for Demonstration Selection via Internal Representations
di: Kato, Mariko, et al.
Pubblicazione: (2025)

Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors
di: Huang, Jing, et al.
Pubblicazione: (2025)

A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models
di: Shu, Dong, et al.
Pubblicazione: (2025)

From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step
di: Deng, Yuntian, et al.
Pubblicazione: (2024)

SPIN: Sparsifying and Integrating Internal Neurons in Large Language Models for Text Classification
di: Jiao, Difan, et al.
Pubblicazione: (2023)

Empowering Small-Scale Knowledge Graphs: A Strategy of Leveraging General-Purpose Knowledge Graphs for Enriched Embeddings
di: Sawczyn, Albert, et al.
Pubblicazione: (2024)

Internal Value Alignment in Large Language Models through Controlled Value Vector Activation
di: Jin, Haoran, et al.
Pubblicazione: (2025)

Internalizing Outcome Supervision into Process Supervision: A New Paradigm for Reinforcement Learning for Reasoning
di: Ding, Fei, et al.
Pubblicazione: (2026)

CROW: Eliminating Backdoors from Large Language Models via Internal Consistency Regularization
di: Min, Nay Myat, et al.
Pubblicazione: (2024)

Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders
di: Jing, Yi, et al.
Pubblicazione: (2026)

Hallucination Detection in LLMs Using Spectral Features of Attention Maps
di: Binkowski, Jakub, et al.
Pubblicazione: (2025)

Revisiting the Scaling Properties of Downstream Metrics in Large Language Model Training
di: Krajewski, Jakub, et al.
Pubblicazione: (2025)

FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs
di: Sawczyn, Albert, et al.
Pubblicazione: (2025)

Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
di: Daheim, Nico, et al.
Pubblicazione: (2024)

Look Inward to Explore Outward: Learning Temperature Policy from LLM Internal States via Hierarchical RL
di: Zhou, Yixiao, et al.
Pubblicazione: (2026)

PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning
di: Zou, Jiaru, et al.
Pubblicazione: (2024)

Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor's Internal States
di: Choi, Yunho, et al.
Pubblicazione: (2026)

ExpeL: LLM Agents Are Experiential Learners
di: Zhao, Andrew, et al.
Pubblicazione: (2023)

MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors
di: Macina, Jakub, et al.
Pubblicazione: (2025)

Better as Generators Than Classifiers: Leveraging LLMs and Synthetic Data for Low-Resource Multilingual Classification
di: Pecher, Branislav, et al.
Pubblicazione: (2026)

Zamba: A Compact 7B SSM Hybrid Model
di: Glorioso, Paolo, et al.
Pubblicazione: (2024)

The Illusion of Progress: Re-evaluating Hallucination Detection in LLMs
di: Janiak, Denis, et al.
Pubblicazione: (2025)

The Zamba2 Suite: Technical Report
di: Glorioso, Paolo, et al.
Pubblicazione: (2024)

mcdok at SemEval-2026 Task 13: Finetuning LLMs for Detection of Machine-Generated Code
di: Skurla, Adam, et al.
Pubblicazione: (2026)

The Problem of Coherence in Natural Language Explanations of Recommendations
di: Raczyński, Jakub, et al.
Pubblicazione: (2023)