Image de couverture de livre

LLMs Should Express Uncertainty Explicitly

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Guo, Junyu, Gu, Shangding, Jin, Ming, Spanos, Costas, Lavaei, Javad
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

StyleBench: Evaluating thinking styles in Large Language Models
par: Guo, Junyu, et autres
Publié: (2025)

Don't Trade Off Safety: Diffusion Regularization for Constrained Offline RL
par: Guo, Junyu, et autres
Publié: (2025)

Few-Shot Test-Time Optimization Without Retraining for Semiconductor Recipe Generation and Beyond
par: Gu, Shangding, et autres
Publié: (2025)

Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
par: Gu, Shangding, et autres
Publié: (2025)

Long Context, Less Focus: A Scaling Gap in LLMs Revealed through Privacy and Personalization
par: Gu, Shangding
Publié: (2026)

Estimation of Concept Explanations Should be Uncertainty Aware
par: Piratla, Vihari, et autres
Publié: (2023)

SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales
par: Xu, Tianyang, et autres
Publié: (2024)

Retrieval Augmented Question Answering: When Should LLMs Admit Ignorance?
par: Wang, Dingmin, et autres
Publié: (2025)

GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning
par: Mavromatis, Costas, et autres
Publié: (2024)

When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation
par: Goren, Shani, et autres
Publié: (2026)

ABBEL: LLM Agents Acting through Belief Bottlenecks Expressed in Language
par: Lidayan, Aly, et autres
Publié: (2025)

Explicit Diversity Conditions for Effective Question Answer Generation with Large Language Models
par: Yadav, Vikas, et autres
Publié: (2024)

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
par: Wang, Yinong Oliver, et autres
Publié: (2025)

Uncertainty quantification in fine-tuned LLMs using LoRA ensembles
par: Balabanov, Oleksandr, et autres
Publié: (2024)

Examining LLMs' Uncertainty Expression Towards Questions Outside Parametric Knowledge
par: Liu, Genglin, et autres
Publié: (2023)

Skin-in-the-Game: Decision Making via Multi-Stakeholder Alignment in LLMs
par: Sel, Bilgehan, et autres
Publié: (2024)

When Should Models Change Their Minds? Contextual Belief Management in Large Language Models
par: Xu, Haoming, et autres
Publié: (2026)

Flaw or Artifact? Rethinking Prompt Sensitivity in Evaluating LLMs
par: Hua, Andong, et autres
Publié: (2025)

Aligning LLMs with Human Uncertainty: A Beta-Bernoulli Calibrator for LLM Forecasting
par: Dai, Hui, et autres
Publié: (2026)

The Alignment Tax: Response Homogenization in Aligned LLMs and Its Implications for Uncertainty Estimation
par: Liu, Mingyi
Publié: (2026)

SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection
par: Liu, Liangxin, et autres
Publié: (2024)

UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Making
par: Duan, Jinhao, et autres
Publié: (2025)

Time-Aware Feature Selection: Adaptive Temporal Masking for Stable Sparse Autoencoder Training
par: Li, T. Ed, et autres
Publié: (2025)

LLMs Should Incorporate Explicit Mechanisms for Human Empathy
par: You, Xiaoxing, et autres
Publié: (2026)

Explicit Multi-head Attention for Inter-head Interaction in Large Language Models
par: Peng, Runyu, et autres
Publié: (2026)

Kernel Language Entropy: Fine-grained Uncertainty Quantification for LLMs from Semantic Similarities
par: Nikitin, Alexander, et autres
Publié: (2024)

Can LLMs Speak For Diverse People? Tuning LLMs via Debate to Generate Controllable Controversial Statements
par: Li, Ming, et autres
Publié: (2024)

Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective
par: Gonzalez, Emmanuel Anaya, et autres
Publié: (2025)

Position: Mechanistic Interpretability Should Prioritize Feature Consistency in SAEs
par: Song, Xiangchen, et autres
Publié: (2025)

MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
par: Huang, Kaixuan, et autres
Publié: (2025)

Explicit Word Density Estimation for Language Modelling
par: Andonov, Jovan, et autres
Publié: (2024)

Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
par: Al-Tawaha, Ahmad, et autres
Publié: (2026)

Calibration Collapse Under Sycophancy Fine-Tuning: How Reward Hacking Breaks Uncertainty Quantification in LLMs
par: Sahoo, Subramanyam
Publié: (2026)

Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search
par: Gu, Yuxian, et autres
Publié: (2025)

Toxicity Detection Should Measure Contextual Harm, Not Text-Intrinsic Badness
par: Berezin, Sergei, et autres
Publié: (2025)

Should You Use Your Large Language Model to Explore or Exploit?
par: Harris, Keegan, et autres
Publié: (2025)

The Remarkable Robustness of LLMs: Stages of Inference?
par: Lad, Vedang, et autres
Publié: (2024)

OUTLINEFORGE: Hierarchical Reinforcement Learning with Explicit States for Scientific Writing
par: Bao, Yilin, et autres
Publié: (2026)

Enhancing LLM Reliability via Explicit Knowledge Boundary Modeling
par: Zheng, Hang, et autres
Publié: (2025)

Visualizing Uncertainty in Translation Tasks: An Evaluation of LLM Performance and Confidence Metrics
par: Park, Jin Hyun, et autres
Publié: (2025)