Search: “models”

Uncovering Understanding-Generation Synergy in Native Unified Multimodal Models: From Representation, Task to System

arXiv:2609.01607v1 Announce Type: new Abstract: While unified multimodal models (UMMs) jointly perform visual understanding and generation within a single model, functional unification does not guaran

safetyarxiv-cs-cv

2 Sept 2026

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AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

DGX agent

arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet

model-releasesarxiv-cs-lg

1 Sept 2026

Do Small Models Use the Law You Give Them? Measuring Context Use on a Bilingual Bangladesh Legal Benchmark

arXiv:2608.30327v1 Announce Type: new Abstract: Fine-tuning can improve legal question-answering accuracy without improving how models use law supplied in context. We study this distinction in bilingu

Evaluating the Semantic Specificity of Representation Steering in Language Models

arXiv:2608.29431v1 Announce Type: new Abstract: Localized Representation Steering (LRS) is widely used to correct reasoning pathologies in large language models. However, standard benchmark evaluation

Looking Again: Measuring Sycophancy in the Reasoning Chains of Multimodal Models Under Pressure

arXiv:2608.28623v1 Announce Type: cross Abstract: Large multimodal reasoning models (LMRMs) are getting increasingly capable, primarily through generating explicit chain-of-thought reasoning before an

Reward-guided Fine-Tuning of One-Step Generative Models via Wasserstein Gradient Flow

arXiv:2608.29647v1 Announce Type: new Abstract: To mitigate the time complexity of generative models, one-step generative models have recently emerged through direct mapping from noise to data in a si

safetyarxiv-cs-lg

TuringLLM: Efficiently Scaling Foundation Models Toward Physical AI

arXiv:2608.30567v1 Announce Type: new Abstract: We present Turing-20B-A2B, a 20B-parameter Mixture-of-Experts language model that activates approximately 2B parameters per token, designed for long-con

Uncertainty of Vision Medical Foundation Models

arXiv:2608.30390v1 Announce Type: new Abstract: Accurate uncertainty estimation is essential for machine learning systems de- ployed in high-stakes domains such as medicine. Traditional approaches pri

researcharxiv-cs-lg

WorldCupArena: Fine-Grained Evaluation of Language Models and Deep-Research Agents on Football Forecasting

arXiv:2607.18084v2 Announce Type: replace Abstract: Predicting a football match before kickoff requires more than knowing past results: a model must use changing information and make a clear predictio

Knowing Before Answering: Decoding Language Models for Reliable RAG

arXiv:2608.27661v1 Announce Type: new Abstract: In Retrieval-Augmented Generation (RAG), retrieval may provide insufficient or conflicting information needed to answer a question. The system should no

Off the Normal Path: Learning Spatial Density Models of Node Mobility

arXiv:2411.10997v2 Announce Type: replace-cross Abstract: We consider the problem of learning models of spatial density functions, representing the steady-state density of mobile nodes moving on a two

Applications

Pruning Laws for Large Language Models

arXiv:2504.04342v2 Announce Type: replace Abstract: Scaling up model parameters and training data consistently improves the performance of large language models (LLMs), but at the cost of rapidly grow

applicationsarxiv-cs-cl

Token-Budget Distillation: Transferring Full-Token Semantics to Compressed Video Vision-Language Models

arXiv:2608.28138v1 Announce Type: new Abstract: Adapting video vision-language models (VLMs) is computationally expensive because video inputs produce a large number of visual tokens, making both fine

Applications

CLAP: Cross-Embodiment Video World Models are Zero-Shot Physical Simulators

arXiv:2608.27406v1 Announce Type: cross Abstract: State-of-the-art action-conditioned video models are typically restricted to a single robot embodiment, preventing them from leveraging the vast corpu

applicationsarxiv-cs-ai

28 Aug 2026

MVC-Bench: Benchmarking Calibration of Medical Vision-Language Models

arXiv:2608.27004v1 Announce Type: new Abstract: Reliable evaluation of vision-language models (VLMs) and medical vision-language models (Medical-VLMs) requires calibrated confidence, particularly unde

28 Aug 2026

Vision-centric generative AI models: A software-hardware perspective

arXiv:2608.27199v1 Announce Type: new Abstract: Vision generative artificial intelligence (AI) has emerged as one of the most rapidly advancing areas of deep learning. The explosion of multimodal mode

28 Aug 2026

Learning Mixtures of Plackett-Luce Models for Multi-Objective Alignment

arXiv:2608.25200v1 Announce Type: cross Abstract: We consider the problem of learning a mixture of k Plackett-Luce models given multi-way ranking responses from annotators that may represent heterogen

safetyarxiv-cs-cl

27 Aug 2026

ADVERSA: Measuring Multi-Turn Guardrail Degradation and Judge Reliability in Large Language Models

arXiv:2603.10068v2 Announce Type: replace-cross Abstract: Most adversarial evaluations of large language model (LLM) safety assess single prompts and report binary pass/fail outcomes, which fails to c

Applications

Data Leakage Inflates Generalizability of Power Outage Prediction Models

arXiv:2608.24665v1 Announce Type: new Abstract: Power outage prediction models are increasingly used in assessments of climate-driven infrastructure risk, yet current evaluation practices obscure whet

applicationsarxiv-cs-lg

DoublesEval: Diagnosing Multi-Agent Tactical Reasoning in Vision-Language Models via Professional Doubles Badminton

arXiv:2608.24439v1 Announce Type: new Abstract: Visual Language Models (VLMs) excel at describing visible scene content but struggle to reason about dynamic multi-agent interactions, where action sema

GlanceWAM: Sparse Test-Time Imagination for World-Action Models

arXiv:2608.23927v1 Announce Type: new Abstract: Video generative models provide rich physical priors for robot learning, yet existing world-action models (WAMs) face a fundamental trade-off: synchrono

Response Renormalization for Critical Deep Equilibrium Models

arXiv:2608.23725v1 Announce Type: new Abstract: Deep Equilibrium Models (DEQs) compute predictions from a hidden representation unchanged by the model update. Training through this equilibrium uses im

TRACE: An Evidence-Grounded Benchmark for Safety Evaluation of Large Reasoning Models

arXiv:2608.24232v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate intermediate reasoning traces that may contain unsafe content, even when their final responses appear safe. Guard

Wait, Wait, Wait... Why Do Reasoning Models Loop?

arXiv:2512.12895v2 Announce Type: replace Abstract: Reasoning models (e.g., DeepSeek-R1) generate long chains of thought to solve harder problems, but they often loop, repeating the same text at low t

Evaluation Awareness in Language Models: Representation, Verbalization, and Control

arXiv:2608.21766v1 Announce Type: cross Abstract: Both capability and safety benchmarks rest upon the assumption that the behavior of language models undergoing a test is informative about their behav

safetyarxiv-cs-ai

EviSafe: Evidence-Grounded Safety Evaluation for Vision-Language Models

arXiv:2608.23313v1 Announce Type: new Abstract: Vision-language model safety benchmarks typically evaluate only final responses: whether a model refuses, warns, or complies. This outcome-level view ca

EXPL-FR: Explaining Face Recognition Models via Vision-Language Alignment

arXiv:2608.21486v1 Announce Type: new Abstract: Deep face recognition (FR) models reach near-saturated accuracy but remain opaque: a practitioner cannot ask which semantic attributes a similarity scor

Quantifying geographic domain shift to decouple the geospatial transferability of human mobility flow generation models

arXiv:2608.21567v1 Announce Type: new Abstract: Human mobility serves as an essential proxy for understanding social, economic, and environmental dynamics in urban systems. Geospatial transferability,

Training-Free Pseudo-Fusion for Composed Image Retrieval with Diffusion Models and Multimodal Large Language Models

arXiv:2608.23102v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) is an emerging paradigm in content-based image retrieval that enables users to formulate compositional queries by combini

researcharxiv-cs-cv

CellPath-Bench: A Multidimensional Benchmark for Whole-Slide Cellular Representations in Pathology Foundation Models

arXiv:2608.21060v1 Announce Type: new Abstract: Pathology foundation models (PFMs) are increasingly used as general-purpose backbones, yet existing benchmarks cannot systematically diagnose their whol

24 Aug 2026

Entity tracking emerges in sub-billion parameter language models and exceeds human performance in naturalistic narratives

arXiv:2608.18083v1 Announce Type: new Abstract: Understanding language requires tracking entities across discourse - i.e., knowing where things are and how they change, even when not explicitly stated

Improving Natural-Language Combinatorial-Optimization Accuracy in Resource-Constrained Language Models via Formal Abstractions

arXiv:2608.18409v1 Announce Type: new Abstract: Combinatorial scheduling poses a significant challenge for language models, requiring them to identify feasible solutions within exponentially large sea

researcharxiv-cs-ai

On the Robustness of Vision-Language Models in Zero-shot Privacy Classification

arXiv:2510.09253v2 Announce Type: replace Abstract: Automatic systems for document understanding require multimodal models that accurately identify sensitive visual content, even in the presence of im

Regularised Iterative Generalised Least Squares with Optimal Selection of the Hyper-Parameter for Identifying Nonlinear Phenomenological Models

arXiv:2608.18742v1 Announce Type: cross Abstract: In some fields currently dominated by empirical approaches, such as state of health (SoH) prediction for lithium-ion batteries, phenomenological model

Score the Algebra, Not the Span: Dimension Reduction for Transfer Operator Models of Dynamical Systems

arXiv:2608.18918v1 Announce Type: new Abstract: Dimension reduction for dynamical systems is standard practice, and the standard route is spectral: model the transfer (Koopman) operator by its leading

Local Ai

Learnware for CSI Feedback: Scene-specific Small Models Can Do Big

arXiv:2608.17760v1 Announce Type: cross Abstract: Intelligent channel state information (CSI) feedback is essential for realizing the high capacity and spectral efficiency goals of future 6G systems,

local-aiarxiv-cs-ai

19 Aug 2026

Towards Zero-Shot Task Transfer with Neurosymbolic World Models

arXiv:2608.17959v1 Announce Type: new Abstract: State-of-the-art model-based reinforcement learning methods learn neural world models that allow policy improvement by planning in a latent space, witho

safetyarxiv-cs-ai

19 Aug 2026

When to Review: Spaced Repetition for Continual Pre-Training of Language Models

arXiv:2608.17530v1 Announce Type: new Abstract: Continual pre-training of large language models must acquire new information without erasing old knowledge. Existing replay methods often choose a globa

19 Aug 2026

CrossView: Can Vision-Language Models Reason Across Cameras?

arXiv:2608.15539v1 Announce Type: new Abstract: Video understanding benchmarks have long centered on single-camera settings, where modern multi-modal language models achieve strong performance across

Local Ai

Large Models for Small Devices: Recent Advances and Empirical Analysis of Edge AI Deployment

arXiv:2608.15693v1 Announce Type: new Abstract: Running large AI models on resource-constrained edge devices requires model compression to reduce model size and computation. What compresses well, howe

local-aiarxiv-cs-ai

SafeGesture: Evaluating Fine-Grained Hand Gesture Understanding in Vision-Language Models through Scenario-Conditioned Safety Interpretation

arXiv:2608.16081v1 Announce Type: new Abstract: Open-weight and frontier vision-language models (VLMs) perform well on general image understanding, but their ability to interpret fine-grained hand ges

What Do Compliance Detectors Read? An Audit of Activation Probes and Guard Models

arXiv:2608.16852v1 Announce Type: new Abstract: Regulatory compliance monitoring in deployed language models is increasingly implemented as a legal and audit control, checking model outputs against wr

Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View

arXiv:2608.14430v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training provides a direct way to align diffusion models with human preferences and task-specific rewards. However, c

17 Aug 2026

EEG-PRISM: Physiologically-Grounded Interpretability of Predictions by EEG Foundation Models

arXiv:2608.13676v1 Announce Type: new Abstract: Objective: Foundation models represent the next advancement in AI for EEG analysis; however current explainable AI techniques provide attribution scores

researcharxiv-cs-lg

17 Aug 2026

EvDiff: Event-Based Video Reconstruction using One-Step Diffusion Models

arXiv:2511.17492v2 Announce Type: replace Abstract: As neuromorphic sensors, event cameras asynchronously record changes in brightness as streams of sparse events with the advantages of high temporal

14 Aug 2026

First-order friction models with bristle dynamics: lumped and distributed formulations

arXiv:2602.09429v3 Announce Type: replace-cross Abstract: Dynamic models, particularly rate-dependent models, have proven effective in capturing the key phenomenological features of frictional process

researcharxiv-cs-ro

13 Aug 2026

How China-Origin Vision-Language Models Move from Refusal to Reframing in State Alignment

arXiv:2608.11816v1 Announce Type: cross Abstract: State-aligned distortion has been documented in China-origin text-based large language models (LLMs), but whether, and in what form, it arises in mult

13 Aug 2026

Localizing Safety Alignment: MLP Layers and Mid-Network Blocks Encode Refusal Behavior in Large Language Models

arXiv:2608.11583v1 Announce Type: new Abstract: Safety alignment in large language models is often treated as a distributed property of the entire network, yet its practical brittleness suggests that