Search: “models”

arXiv:2608.07648v1 Announce Type: cross Abstract: Sampling high-dimensional probability distributions is a central task in scientific computing, with applications ranging from Bayesian inference to st

tutorialsarxiv-cs-lg

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Listen, See and Track: Spatio-Temporal Audio-Visual Sound Event Reasoning for Omni-Modal Language Models

DGX agent

arXiv:2608.09435v1 Announce Type: new Abstract: Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time. Yet exi

model-releasesarxiv-cs-ai

11 Aug 2026

LLMs Remember First, Forget Last: Dual-Process Interference in Large Language Models

arXiv:2603.00270v3 Announce Type: replace-cross Abstract: Large language models can process millions of tokens, yet how they handle conflicting information within context remains poorly understood. Fr

safetyarxiv-cs-ai

LookME: Lookup-Based Multimodal Embeddings for Layer Injection in Vision-Language Models

arXiv:2607.16305v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved strong progress in multimodal understanding. However, scaling dense or sparse Mixture-of-Experts (

Tutorials

MaxModShift: Model Privacy via Designed Shifts

arXiv:2608.09328v1 Announce Type: new Abstract: Model learning by an eavesdropper is treated as an estimation problem in a federated environment. The Fisher Information Matrix for the eavesdropper's e

tutorialsarxiv-cs-lg

Multilingual Agent-Based World Modeling for Social Science

arXiv:2512.07195v2 Announce Type: replace-cross Abstract: Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly mon

One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training

arXiv:2608.09403v1 Announce Type: new Abstract: Whole slide images (WSIs) in digital histopathology are acquired at discrete magnification levels encoding complementary diagnostic information from glo

researcharxiv-cs-cv

Performance of large language models in the optical diagnosis of colorectal polyps

arXiv:2608.07543v1 Announce Type: cross Abstract: Background and Study Aims: Accurate optical diagnosis of colorectal polyps guides resection strategy and surveillance, with multimodal large language

ReMIND: Orchestrating Modular Large Language Models for Controllable Serendipity A REM-Inspired System Design for Emergent Creative Ideation

arXiv:2601.07121v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used not only for problem solving but also for creative ideation; however, generating ideas that

Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification

arXiv:2608.09512v1 Announce Type: new Abstract: Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and tempo

Toward Mask Annotation-Free Surgical Instrument Segmentation from Endoscopic Images Using Text-Prompted Segment Anything Model 3 (SAM3)

model-releasesarxiv-cs-cv

arXiv:2608.08844v1 Announce Type: new Abstract: Surgical instrument segmentation is a fundamental task for computer-assisted interventions, yet most existing methods rely on pixel-level annotations or

CellWorld: From Gene-Level Reconstruction to Latent Cell Prediction in Spatial Transcriptomics Foundation Models

arXiv:2608.06659v1 Announce Type: new Abstract: This paper shows that latent-space predictive pretraining can provide a scalable route to foundation models for spatial transcriptomics. Existing spatia

Convergence of Diffusion Models Under the Manifold Hypothesis in High-Dimensions

arXiv:2409.18804v3 Announce Type: replace-cross Abstract: Denoising Diffusion Probabilistic Models (DDPM) are powerful state-of-the-art methods used to generate synthetic data from high-dimensional da

Depth-Wise Probing and Pruning of the Planning Token in a Driving Vision-Language-Action Model

arXiv:2608.07361v1 Announce Type: cross Abstract: Vision-language-action (VLA) models route driving decisions through a deep language model, but it is unclear how much of that depth the action itself

researcharxiv-cs-cv

Faster Query-Key Learning Sharpens Attention in Self-Attention Models

model-releasesarxiv-cs-lg

arXiv:2608.06776v1 Announce Type: new Abstract: A standard self-attention layer consists of two interacting circuits: the query-key circuit that governs attention allocation, and the output-value circ

How Molecular Generative Models Organize Molecular Identity

arXiv:2608.06956v1 Announce Type: new Abstract: Generative models for matter are often evaluated as samplers over output representations, and their latent spaces are commonly used as proxies for navig

Separating Decision-Rule Misalignment from Readout-Coverage Limitations in Speech Language Models

arXiv:2608.06409v1 Announce Type: cross Abstract: Speech language models are increasingly evaluated on paralinguistic tasks by the accuracy of prompted answers, but answer accuracy combines failures a

AI Playing Business Games: Benchmarking Large Language Models on Managerial Decision-Making in Dynamic Simulations

arXiv:2509.26331v2 Announce Type: replace Abstract: The rapid advancement of LLMs sparked significant interest in their potential to augment or automate managerial functions. One of the most recent tr

An Early Warning of Emerging Biosecurity Risks in Frontier LLMs

model-releasesarxiv-cs-cl

arXiv:2607.18056v2 Announce Type: replace Abstract: Frontier large language models (LLMs) are increasingly integrated into scientific workflows, yet their growing biological capabilities may outpace c

Clinician input steers AI toward accurate and harmful recommendations

model-releasesarxiv-cs-lg

arXiv:2603.14158v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are entering clinical workflows, yet evaluations rarely assess how clinician reasoning shapes model behavior duri

DreamGuard: Efficient Runtime Guardrail for LLM Agents via Risk-Aware World Model

arXiv:2608.05695v1 Announce Type: new Abstract: As large language model (LLM) agents increasingly invoke external tools and interact with real-world systems, unsafe actions may cause irreversible cons

safetyarxiv-cs-ai

LAWM-3D: Learning 3D-Aware Latent Actions from Human Videos for Generalizable Robot World Models

arXiv:2608.05706v1 Announce Type: new Abstract: World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied int

safetyarxiv-cs-cv

On the Anisotropy of Score-Based Generative Models

arXiv:2510.22899v2 Announce Type: replace Abstract: We investigate the role of network architecture in shaping the inductive biases of modern score-based generative models. To this end, we introduce t

The Low Frequency Trap: Video Language Models Fail at Simple Event Bookkeeping

arXiv:2608.06361v1 Announce Type: new Abstract: Real-world video benchmarks provide broad coverage, but their fixed clips entangle event count, rate, duration, and visual complexity, making failure mo

Toward Deployable Bangla Sign Language Recognition with Expert-Validated Data and a Lightweight Attention-Based Model

arXiv:2608.06252v1 Announce Type: cross Abstract: Deaf and hard-of-hearing people in Bangladesh communicate mainly through Bangla Sign Language (BdSL). Automatic BdSL recognition on personal devices c

Applications

Uncertainty-Aware World Model for Aerial Image-Goal Navigation

arXiv:2608.05597v1 Announce Type: new Abstract: Aerial image-goal navigation requires an unmanned aerial vehicle (UAV) to reach a target location specified by a goal image. Existing world-model-based

applicationsarxiv-cs-cv

XEWorld: Can Action-Conditioned World Models Generalize to Unseen Robot Embodiments?

arXiv:2608.05799v1 Announce Type: cross Abstract: Action-conditioned world models are promising learned simulators for robotic manipulation, yet evaluating them exclusively on training robots fails to

safetyarxiv-cs-cv

Convergence and Stability Analysis of Self-Consuming Generative Models with Heterogeneous Human Curation

arXiv:2511.09002v3 Announce Type: replace-cross Abstract: Self-consuming generative models have received significant attention over the last few years. In this paper, we study a self-consuming generat

Do LLMs Know What Is Private Internally? Probing and Steering Contextual Privacy Norms in Large Language Model Representations

arXiv:2604.00209v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in high-stakes settings, yet they frequently violate contextual privacy by disclosing private

researcharxiv-cs-cl

EuroExec: Frontier Language Models Fall Short of Expert Judgment on European Executive Decision Tasks

arXiv:2608.04549v1 Announce Type: cross Abstract: Frontier LLMs are increasingly put to use on open-ended complex questions, different in nature from the ones they are typically evaluated on. We dedic

Evaluating Theory of Mind in Reasoning Models: Robustness over Reasoning

arXiv:2608.04646v1 Announce Type: new Abstract: Large language models (LLMs) have recently shown strong performance on Theory of Mind (ToM) tests, prompting debate about the nature and validity of the

researcharxiv-cs-cl

Explicit Language Memory for Long-Horizon Planning in Vision-Language-Action Models

arXiv:2608.04765v1 Announce Type: cross Abstract: Vision-language-action (VLA) models provide a unified paradigm for connecting visual perception, language understanding, and robotic control. However,

Helping Music Co-Creation Agents 'Listen' Well: Hierarchical Self-Supervised World Models for Understanding and Generation

model-releasesarxiv-cs-lg

arXiv:2608.04378v1 Announce Type: cross Abstract: Collaborative music agents need internal representations rich enough to support both understanding and generation, yet flexible enough for a workflow

Koopman-Based Nonlinear Identification and Model Predictive Control of a Turbofan Engine

arXiv:2604.01730v2 Announce Type: replace Abstract: This paper investigates Koopman operator-based approaches for multivariable control of a two-spool turbofan engine. A physics-based component-level

LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content

model-releasesarxiv-cs-cv

arXiv:2410.10783v4 Announce Type: replace Abstract: The large-scale training of multi-modal models on data scraped from the web has shown outstanding utility in infusing these models with the required

MarsCast: Transfer Learning of AI Weather Foundation Models to Planetary Atmospheres

arXiv:2608.05054v1 Announce Type: cross Abstract: We investigate the transferability of Earth weather foundation models to planetary atmospheres by adapting the GraphCast graph neural weather forecast

Mind-VLA: Instruction-Aware Spatial Representation Alignment for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2608.04633v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) methods improve generalization by aligning their representations with 3D scene geometry. However, these methods are

ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation

arXiv:2608.04436v1 Announce Type: new Abstract: Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understandi

safetyarxiv-cs-cv

When Absence Is Evidence: Evaluating Completeness-Sensitive Negative Reasoning in Large Language Models

arXiv:2608.04591v1 Announce Type: cross Abstract: Large language models (LLMs) are often asked whether something is absent from a record, list, or retrieved context. Yet non-observation licenses a neg

Local Ai

Any-OPD: Heterogeneous On-Policy Distillation for Flow-Matching Models via Representation-Space Bridging

arXiv:2608.03316v1 Announce Type: cross Abstract: On-policy distillation, in which a teacher corrects samples that the student itself generates, presupposes that the two models speak the same language

local-aiarxiv-cs-cv

ArtECulture: Benchmarking Culture-Conditioned Visual Emotion Understanding in Multimodal Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.03358v1 Announce Type: new Abstract: Existing visual emotion understanding methods typically ignore cultural variations in emotional perception. We introduce culture-conditioned visual emot

BOW: Training Language Models to Reason Over Plausible Next Words

arXiv:2506.13502v3 Announce Type: replace Abstract: Next-word prediction (NWP) trains language models against a single observed continuation, even though many contexts admit multiple plausible next wo

safetyarxiv-cs-cl

Can Large Language Models Recover Semantic Optimization Opportunities That Compilers Miss?

arXiv:2608.03983v1 Announce Type: cross Abstract: Optimizing compilers miss profitable transformations when their enabling semantics are absent from the analyzed program representation. We ask whether

Can Training Logs Make Model Comparisons More Precise?

arXiv:2608.02705v1 Announce Type: cross Abstract: Comparing stochastically trained models requires estimating both a performance difference and its uncertainty from repeated runs. We study whether tra

Applications

Cross-Model KV Cache Transfer in LLM Families: A Closed-Form Linear Mapping for Prefill Reuse

arXiv:2608.03893v1 Announce Type: new Abstract: Production deployments often swap between different-sized models in a family for cost-quality cascading, mid-conversation switching, and routing, and ea

applicationsarxiv-cs-lg

Cura 1T: Specialized Model for Agentic Healthcare

arXiv:2607.15314v2 Announce Type: replace Abstract: Healthcare AI agents handle patient consultation, clinical reasoning over text and images, interactive diagnosis, and electronic health record (EHR)

DUD: Decoupled Update Dynamics for Reliable Uncertainty Quantification in Large Language Models

arXiv:2608.03411v1 Announce Type: new Abstract: Accurate Uncertainty Quantification (UQ) is critical for reliable deployment of Large Language Models (LLMs), yet traditional probability-based metrics

researcharxiv-cs-cl

Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement

arXiv:2608.03733v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-