Academic
Academic
Towards Reliable Truth-Aligned Uncertainty Estimation in Large Language Models
arXiv:2604.00445v1 Announce Type: new Abstract: Uncertainty estimation (UE) aims to detect hallucinated outputs of large language models (LLMs) to improve their reliability. However, UE metrics …
Oblivion: Self-Adaptive Agentic Memory Control through Decay-Driven Activation
arXiv:2604.00131v1 Announce Type: new Abstract: Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual …
Locally Confident, Globally Stuck: The Quality-Exploration Dilemma in Diffusion Language Models
arXiv:2604.00375v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) theoretically permit token decoding in arbitrary order, a flexibility that could enable richer exploration of …
Does Unification Come at a Cost? Uni-SafeBench: A Safety Benchmark for Unified Multimodal Large Models
arXiv:2604.00547v1 Announce Type: new Abstract: Unified Multimodal Large Models (UMLMs) integrate understanding and generation capabilities within a single architecture. While this architectural unification, driven by …
Semantic Shifts of Psychological Concepts in Scientific and Popular Media Discourse: A Distributional Semantics Analysis …
arXiv:2604.00017v1 Announce Type: new Abstract: This article examines semantic shifts in psychological concepts across scientific and popular media discourse using methods of distributional semantics applied …
Transformer self-attention encoder-decoder with multimodal deep learning for response time series forecasting and digital twin …
arXiv:2604.01712v1 Announce Type: new Abstract: The wind-induced structural response forecasting capabilities of a novel transformer methodology are examined here. The model also provides a digital …
Adversarial Moral Stress Testing of Large Language Models
arXiv:2604.01108v1 Announce Type: new Abstract: Evaluating the ethical robustness of large language models (LLMs) deployed in software systems remains challenging, particularly under sustained adversarial user …
TR-ICRL: Test-Time Rethinking for In-Context Reinforcement Learning
arXiv:2604.00438v1 Announce Type: new Abstract: In-Context Reinforcement Learning (ICRL) enables Large Language Models (LLMs) to learn online from external rewards directly within the context window. …
ASCAT: An Arabic Scientific Corpus and Benchmark for Advanced Translation Evaluation
arXiv:2604.00015v1 Announce Type: new Abstract: We present ASCAT (Arabic Scientific Corpus for Advanced Translation), a high-quality English-Arabic parallel benchmark corpus designed for scientific translation evaluation …
Self-Routing: Parameter-Free Expert Routing from Hidden States
arXiv:2604.00421v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) layers increase model capacity by activating only a small subset of experts per token, and typically rely on …