Search: “models”

arXiv:2607.21910v2 Announce Type: replace Abstract: World models let agents plan against predicted physical state, but that state drifts; re-observation is costly and delayed, and repair can fail. We

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7 Aug 2026

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Hardware

AMD acquires Taalas to hardwire AI models into silicon

DGX agent

Advanced Micro Devices Inc. said today it has agreed to buy Taalas Inc., a Toronto startup that hardwires artificial intelligence models directly into silicon, in a deal that pushes the chipmaker deep

hardwaresiliconangle

6 Aug 2026

AudioDER: A Deduplication-Enhanced Reasoning Dataset for Post-Training Large Audio-Language Models

arXiv:2606.14591v2 Announce Type: replace-cross Abstract: Recent advances in pretrained large audio-language models (LALMs) have demonstrated strong capabilities across speech, sound, and music. To ad

researcharxiv-cs-ai

Causal Evidence Extraction and Triangulation in Crisis Reports using Large Language Models: A ReliefWeb-based Study

model-releasesarxiv-cs-cl

arXiv:2608.04576v1 Announce Type: new Abstract: Humanitarian reports are long, noisy, and multi-topic, making it difficult to consolidate decision-relevant causal evidence. We present a ReliefWeb stud

Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability

arXiv:2503.14833v2 Announce Type: replace-cross Abstract: One of the bottlenecks in robotic intelligence is the instability of neural network models. This leads to risks when applying intelligence in

GeoReward: Mitigating Contextual Variable Overestimation in Vision-Language Models for Cross-Market Preference Prediction

arXiv:2608.04504v1 Announce Type: cross Abstract: Vision-language models excel in many multimodal tasks but remain prone to a subtle yet impactful failure mode: they tend to overestimate dominant visu

Hardware

Into the Omniverse: How Open World Models Push the Frontier of Physical AI

In July, NVIDIA joined more than 200 companies and organizations in signing “Open Weights and American AI Leadership,” an open letter arguing that AI leadership will be measured not by any single fron

hardwarenvidia-blog

Kitchen Robotic Manipulation utilizing Foundation Models

model-releasesarxiv-cs-ro

arXiv:2608.04042v1 Announce Type: new Abstract: Deploying robots in everyday human environments requires perception systems that are both robust and adaptable to diverse, dynamic conditions. In this w

Poly-OPD: Heterogeneous Multi-Teacher On-Policy Distillation for Capability-Selectable Flow Models

arXiv:2608.04349v1 Announce Type: new Abstract: Leading open text-to-image models often carry complementary strengths: one may lead on preference-aligned aesthetics while another follows compositional

Understanding Fault Tolerance of Adversarially Robust Pruned Models

arXiv:2608.04173v1 Announce Type: new Abstract: Deep neural networks (DNNs) deployed on resource-constrained neuromorphic hardware face three concurrent challenges: the need for model compression thro

researcharxiv-cs-lg

UniWorld-View: Large-Baseline View Synthesis via Video Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2608.04701v1 Announce Type: new Abstract: The abundance of casually captured monocular videos and images on social media provides a valuable source for immersive content creation, where generati

Unleashing the Potential of Vision-Language Models for Generalizable AI-Generated Image Detection

arXiv:2608.04935v1 Announce Type: new Abstract: Recent work has shown that a simple linear probe on frozen representations from modern vision foundation models (VFMs) can achieve state-of-the-art AIGI

Attribute-based Undetectable Watermarking for Generative AI Models

arXiv:2608.03174v1 Announce Type: cross Abstract: Generative AI systems increasingly produce content whose provenance is difficult to verify, motivating watermarking techniques for identifying model-g

Local Ai

GSTEP: Global Spatio-Temporal Density-Driven Visual Token Pruning for Efficient Video Large Language Models

arXiv:2608.03083v1 Announce Type: cross Abstract: Video large language models (VideoLLMs) achieve strong video understanding performance, but their inference remains expensive due to the large number

local-aiarxiv-cs-cl

How Should Vision-Language-Action Models Use Proprioceptive State?

arXiv:2608.03052v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models almost universally take robot proprioceptive state as input, yet wire it in incompatible ways -- serialized i

researcharxiv-cs-ro

MambaTS: Improved Selective State Space Models for Long-term Time Series Forecasting

arXiv:2405.16440v2 Announce Type: replace-cross Abstract: In recent years, Transformers have become the de-facto architecture for long-term time series forecasting (LTSF), yet they face challenges ass

Neural Networks with Local Converging Inputs for Efficient Options Pricing Models

model-releasesarxiv-cs-lg

arXiv:2608.02778v1 Announce Type: new Abstract: We present a novel application of Neural Networks with Local Converging Inputs (NNLCI) to improve the efficiency of existing numerical methods for prici

On the Diversity of Analogy Making in Large Language Models

arXiv:2608.03233v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable potential for analogy making, a core cognitive capability that drives novelty and creativity.

Poisoning Prompt-Guided Sampling in Video Large Language Models

arXiv:2509.20851v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) are increasingly deployed as automated moderators on user-generated video platforms, where a few unwatched s

Toward Understanding the Transferability of Adversarial Suffixes in Large Language Models

arXiv:2510.22014v2 Announce Type: replace-cross Abstract: Discrete optimization-based jailbreaking attacks on large language models aim to generate short, nonsensical suffixes that, when appended onto

researcharxiv-cs-ai

When Refusal Looks Safe: The Refusal-Cue Shortcut in Safety Guard Models

model-releasesarxiv-cs-ai

arXiv:2608.03201v1 Announce Type: new Abstract: Safety guards are widely used to filter harmful content and are typically trained via supervised fine-tuning on labeled prompt-response pairs. We audit

An Embedded RISC-V Evaluation of Kolmogorov--Arnold Networks in Hard-Constrained Recurrent Physics-Informed Models

model-releasesarxiv-cs-lg

arXiv:2608.00737v1 Announce Type: new Abstract: Hard-constrained recurrent physics-informed networks (HRPINNs) embed known dynamics inside a recurrent numerical integrator and restrict a neural branch

Applications

Can Urban Blight Be Accessed with Vision-language Models: A Case Study in Detroit

arXiv:2608.01753v1 Announce Type: new Abstract: Addressing urban blight has seen increased focus in the past 15 years. Assessing urban blight is essential for guiding urban planning, targeting rehabil

applicationsarxiv-cs-cv

Tutorials

Exemplars in Disguise: Pure Exemplar Models Mimic Abstraction-First Learning

arXiv:2608.00821v1 Announce Type: new Abstract: Whether idiosyncratic, item-specific knowledge is learned before abstract class-level generalizations, or vice versa, is a central question in language

tutorialsarxiv-cs-cl

Latency-Tolerant Cloud-Edge Collaborative Vision-Language-Action Models via Emergent Representational Specialization

model-releasesarxiv-cs-ro

arXiv:2608.00569v1 Announce Type: new Abstract: Deploying billion-parameter Vision-Language-Action (VLA) policies on mobile robots creates a systems conflict: semantic reasoning benefits from cloud GP

Morphology Aware Reversible Semantic Tokenization and Hierarchical Word Composition for Tamil Language Models

model-releasesarxiv-cs-cl

arXiv:2608.01153v1 Announce Type: new Abstract: Statistical subword tokenizers can process arbitrary text, but their units need not align with lexical or grammatical structure. This is especially impo

ReACT-CLIP: Response-Aware Test-Time Defense for Vision--Language Models

arXiv:2608.01067v1 Announce Type: new Abstract: Training-free test-time defenses offer a practical way to improve the adversarial robustness of CLIP-style vision--language models without modifying the

Test-time Adaptation of Pelvic Bone Segmentation Models via Dynamic Reliability-Guided

arXiv:2608.00510v1 Announce Type: new Abstract: Reliable pelvic bone segmentation (PBS) from CT is essential for robot-assisted pelvic trauma surgery, yet deploying a source-trained model to a new hos

TS-Reasoner: Aligning Time Series Foundation Models with LLM Reasoning

arXiv:2510.03519v2 Announce Type: replace Abstract: Time series reasoning is crucial to decision-making in diverse domains, including finance, energy, and scientific discovery. While existing time ser

safetyarxiv-cs-cl

World Action Models in Real Time: An Empirical Study of Smooth Execution via Asynchronous Deployment

arXiv:2608.01880v1 Announce Type: new Abstract: World Action Models generate fixed-horizon action chunks through iterative denoising, creating substantial inference latency that can cause pauses, stal

safetyarxiv-cs-ro

Do Medical Foundation Models Generalize on the African Brain?

arXiv:2607.28771v1 Announce Type: new Abstract: Medical foundation models (FMs) are increasingly used for brain MRI analysis. However, their evaluation remains dominated by high-resource datasets, lea

Evidence-Type Competition: When Can Interventional Data Teach Language Models Causal Direction?

arXiv:2607.29484v1 Announce Type: new Abstract: Interventional data is widely regarded as the gold standard for teaching models causal reasoning. We test this assumption in a fully controlled syntheti

Fracture Risk Prediction in Adults Over 50 Years Old Using DXA and EHR: Comparison of Traditional and Machine Learning Models in Two Large Cohorts

arXiv:2607.28671v1 Announce Type: cross Abstract: Accurate fracture risk prediction is important for osteoporosis management, but commonly used clinical tools may not fully use information available i

researcharxiv-cs-lg

Geographically Weighted Surrogate Models for Rapid Small-Area Chronic Disease Estimation

model-releasesarxiv-cs-lg

arXiv:2607.28655v1 Announce Type: cross Abstract: Small-area estimation (SAE) enables researchers and policymakers to identify spatial disparities in health outcomes, but survey-based SAE products car

Tutorials

TransMem: Transforming Hidden States into Memory for Large Language Models

arXiv:2607.29032v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting

tutorialsarxiv-cs-cl

Transpiler Autotuning with Predictive Models for Quantum Circuit Optimization

arXiv:2607.29145v1 Announce Type: cross Abstract: Quantum software engineering is an emerging research field focusing on efficiently embedding the quantum programming paradigm into existing software e

researcharxiv-cs-lg

Agents

Belief Coevolution in a Social Network of Generalist and Specialist Large Language Models

arXiv:2607.27512v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in multi-agent environments. However, the processes by which beliefs form and propagate among int

agentsarxiv-cs-cl

Energy-Driven Adaptive Visual Token Pruning for Efficient Vision-Language Models

arXiv:2603.05950v2 Announce Type: replace Abstract: Visual token reduction is critical for accelerating Vision-Language Models (VLMs), since visual inputs are represented as token sequences that intro

Hardware

FARI: Robust One-Step Inversion for Watermarking in Diffusion Models

arXiv:2607.26723v1 Announce Type: cross Abstract: Inversion-based watermarking is a promising approach to authenticate diffusion-generated images, yet practical use is bottlenecked by inversion that i

hardwarearxiv-cs-ai

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models

arXiv:2607.28077v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models, but prompt groups with identical rol

Hardware

ReToken: One Token to Improve Vision-Language Models for Visual Retrieval

arXiv:2607.28627v1 Announce Type: new Abstract: Long visual context poses a challenge for vision-language models: performance degrades as the number of distractors grows, and processing all tokens at

hardwarearxiv-cs-cv

Test-Time Backdoor Detection for Object Detection Models

arXiv:2503.15293v2 Announce Type: replace Abstract: Object detection models are vulnerable to backdoor attacks, where attackers poison a small subset of training samples by embedding a predefined trig

Where and When to Commit: Candidate-Aware Decoding for Diffusion Language Models

arXiv:2607.28166v1 Announce Type: new Abstract: Diffusion language models (DLMs) expose a provisional prediction at every denoising step, creating an opportunity for generation-time early exit that st

Applications

Automated Multilabel Mpox Research Classification with Explainable Transformer Models

arXiv:2607.26700v1 Announce Type: new Abstract: The Mpox outbreak remains a serious public health issue, with the WHO (World Health Organization) reporting increasing cases in some regions. Research o

applicationsarxiv-cs-cl

Tutorials

CalTwin: Towards Calibrated, Shift-Robust Medical World Models via Fisher-Information Regularisation

arXiv:2607.26752v1 Announce Type: new Abstract: Medical world models aim to learn a latent state of patient or organ physiology and a transition function that forecasts how that state evolves under in

tutorialsarxiv-cs-lg

CG-World: A Large-Scale World-State Dataset and Protocol for World Models

arXiv:2607.26452v1 Announce Type: cross Abstract: World models must learn the joint dynamics of states, actions, events, and observations, yet existing video, robotics, and simulation datasets usually

Classification of Disease from Lungs X-ray Images using VGG16, VGG19 and ResNet50 Models

arXiv:2607.26580v1 Announce Type: new Abstract: With the increase in the number of cases related to respiratory diseases, there is an urgent need to detect them early and diagnose them accurately. Con

Local Ai

From Keypoints to Predictive Distributions: Post-Hoc Uncertainty for YOLO-Pose Models

arXiv:2607.26921v1 Announce Type: new Abstract: YOLO-Pose models provide efficient keypoint localization, but do not quantify the associated spatial uncertainty. We introduce a lightweight post-hoc pr

local-aiarxiv-cs-cv