Leaderboards, eval harnesses and ablations — the contested business of deciding which model is actually better.
arXiv:2609.24243v3 Announce Type: replace Abstract: Reinforcement learning (RL) has substantially improved the reasoning capabilities of vision-language models (VLMs), yet it can induce chain-of-thou...
arXiv:2603.07973v2 Announce Type: replace-cross Abstract: Hierarchical multi-robot exploration decouples frontier allocation from local navigation, making systems brittle in dynamic environments. Wit...
arXiv:2603.13023v3 Announce Type: replace-cross Abstract: Training capable software engineering (SWE) agents demands large-scale, executable, and verifiable environments that provide dynamic feedback...
arXiv:2603.09983v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models enable scalable performance but face severe memory constraints on edge devices. Existing offloading strategie...
arXiv:2605.31196v2 Announce Type: replace-cross Abstract: Safe human--robot collaboration requires more than visual description: a monitor must determine whether the robot body is safely separated, a...
arXiv:2610.20959v2 Announce Type: replace-cross Abstract: Answering questions over heterogeneous data means combining evidence from files, databases, documents and the web. Data agents automate this,...
arXiv:2610.31679v1 Announce Type: new Abstract: Large language models are increasingly used as math tutors, raising two questions: can a single LLM detect a student's error, diagnose the underlying m...
arXiv:2610.31684v1 Announce Type: new Abstract: Knowledge Graphs (KGs) have been popularized during the last few decades and are increasingly constructed and consumed by Large Language Models (LLMs)....
arXiv:2610.31723v1 Announce Type: new Abstract: This article introduces Latin Modern BERT (LAMB), an encoder for the Latin language based on the ModernBERT architecture, pretrained in two phases on m...
arXiv:2610.32055v1 Announce Type: new Abstract: Large language models (LLMs) often exhibit sycophancy, altering their answers to align with user suggestions even on objective factual and reasoning ta...
arXiv:2610.32144v1 Announce Type: new Abstract: When a language model is asked whether its own answer is correct, three languages are involved: that of the question, that requested for the answer, an...
arXiv:2610.32441v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly capable of supporting scientific workflows, but their capabilities across diverse research activitie...
arXiv:2610.31838v1 Announce Type: new Abstract: This paper introduces Sense-Aligned Grounding Evaluation (SAGE), a unified 10-candidate image-selection benchmark that reformulates VWSD, VerSe, and Wi...
arXiv:2610.31713v1 Announce Type: cross Abstract: Advances in Omni-modal Large Language Models (OLLMs) have enabled increasingly seamless human-AI interaction, but their unified processing of heterog...
arXiv:2610.31862v1 Announce Type: cross Abstract: This article provides an introduction to the mathematical foundations and algorithmic frameworks used to align Large Language Models (LLMs) with huma...
arXiv:2610.26819v2 Announce Type: replace Abstract: Real-world decision problems combine two qualitatively different kinds of constraints: requirements that must be satisfied, called hard constraints...
arXiv:2610.31835v1 Announce Type: new Abstract: Temporary traffic control redirects vehicles through work zones, requiring automated vehicles to connect an interpretation of the visible devices to a...
arXiv:2610.31848v1 Announce Type: new Abstract: Imaging Flow Cytometry (IFC) generates large multispectral datasets, yet the need for expert annotations bottlenecks the development of supervised deep...
arXiv:2610.32207v1 Announce Type: new Abstract: Continual survival analysis on whole-slide images (WSIs) requires models to integrate knowledge from sequentially arriving cancer cohorts while preserv...
arXiv:2610.32222v1 Announce Type: new Abstract: Reinforcement learning has gained attention for improving action-conditioned world models (ACWMs), as it enables reward-driven optimization of visual q...