Search: “inference”

UniMem: Unifying Multimodal Memory and Control for Vision-Language-Action Models

arXiv:2608.22869v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models have leveraged internet-scale pretraining and task-focused finetuning to achieve strong performance on long-

safetyarxiv-cs-cv

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding

DGX agent

arXiv:2607.14935v2 Announce Type: replace Abstract: Recent advances in video understanding have spanned motion, long video, and streaming interaction, driving this field toward real-world applications

model-releasesarxiv-cs-cv

25 Aug 2026

VIG: Visual Information Gain as a Reward Signal for Multimodal Chain-of-Thought Compression

arXiv:2608.21883v1 Announce Type: new Abstract: Multimodal large reasoning models often rely on long Chain-of-Thought (CoT) traces in which a substantial fraction of tokens, such as repeated visual de

safetyarxiv-cs-cv

VikPath: A Vision Kansformer Framework for Effective Obstacle Avoidance in Self-Supervised Pathfinding

arXiv:2608.22675v1 Announce Type: new Abstract: Pathfinding is a fundamental problem in artificial intelligence and autonomous systems. Traditional heuristic-based algorithms, such as A*, rely on pred

agentsarxiv-cs-ro

VisAdj: Learning Adjacency Matrices from Node-Link Images

arXiv:2608.21825v1 Announce Type: new Abstract: Learning adjacency matrices from node-link images is a fundamental problem for recovering structured graph information from visual observations. Existin

researcharxiv-cs-ai

What actually runs: a measurement study of language model placement and decode speed on the Apple Neural Engine

arXiv:2608.22110v1 Announce Type: new Abstract: We ask what gets a language model onto the Apple Neural Engine (ANE) and what makes it fast there, and we answer with three measurements. We sweep a 64-

What AstroPT knows about galaxies, and what that can teach us about LLMs

arXiv:2608.22614v1 Announce Type: new Abstract: Interpretability research increasingly asks when concepts emerge during training and whether linear probes recover real structure, but in language model

researcharxiv-cs-lg

What Does Activation Steering Control? Attribution Across Answer Encodings and Output-Sensitive Subspaces

arXiv:2608.22985v1 Announce Type: new Abstract: Activation steering is often evaluated under the answer encoding used to construct the direction. A reported gain may reflect the intended judgment or c

researcharxiv-cs-cl

What Memory Composition Does Not Tell Us About Anomaly Detection

arXiv:2608.23295v1 Announce Type: new Abstract: Memory-based anomaly detectors store nominal training patches and score test patches against this memory. A patch selected for coverage therefore become

local-aiarxiv-cs-cv

What Models Know, How Well They Know It: Knowledge-Weighted Fine-Tuning for Learning When to Say 'I Don't Know'

arXiv:2604.05779v2 Announce Type: replace-cross Abstract: While large language models (LLMs) demonstrate strong capabilities across diverse user queries, they still suffer from hallucinations, often a

researcharxiv-cs-ai

What Remains Normal? Clean Images Miss Useful Near-Defect Normal Patches for Anomaly Detection

arXiv:2608.23299v1 Announce Type: new Abstract: Memory-based anomaly detectors store nominal training patches and score test patches against this memory. A patch selected for coverage therefore become

local-aiarxiv-cs-cv

Whole-Body Bilateral Teleoperation with Multi-Stage Object Parameter Estimation for Wheeled Humanoid Locomanipulation

model-releasesarxiv-cs-ro

arXiv:2508.09846v2 Announce Type: replace Abstract: This paper presents an object-aware whole-body bilateral teleoperation framework for wheeled humanoid loco-manipulation. This framework combines who

XIT: Exploration and Exploitation Informed Trees for Active Gas Distribution Mapping in Unknown Environments

arXiv:2602.13739v2 Announce Type: replace Abstract: Mobile robotic gas distribution mapping (GDM) provides critical situational awareness during emergency responses to hazardous gas releases. However,

agentsarxiv-cs-ro

A Hybrid Edge Cloud Digital Twin for Welfare-Constrained Control in Poultry Production

arXiv:2608.20367v1 Announce Type: cross Abstract: Poultry production operates under tightly coupled environmental and biological dynamics, yet commercial climate control remains largely heuristic, lim

local-aiarxiv-cs-ai

A Survey on Foundations and Frontiers of Multimodal Agentic Frameworks: Techniques and Applications

arXiv:2608.20379v1 Announce Type: new Abstract: Advances in large language models (LLMs) have fueled a wave of research into agency: the ability to reason, plan, and act. This effort has produced agen

agentsarxiv-cs-ai

AgentOCR: Reimagining Agent History via Optical Self-Compression

arXiv:2601.04786v3 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) enable agentic systems trained with reinforcement learning (RL) over multi-turn interaction, b

agentsarxiv-cs-ai

AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning

arXiv:2508.14313v4 Announce Type: replace-cross Abstract: Test-time scaling strategies for Large Language Models predominantly rely on either reinforcement learning with sparse outcome rewards or sear

safetyarxiv-cs-ai

Amortized Bandwidth Learning for Kernel Density Estimation under Logarithmic Score

arXiv:2608.20445v1 Announce Type: new Abstract: Kernel density estimation converts finite samples into probability densities, but its performance depends critically on bandwidth selection. Classical s

Automated Trajectory Evaluation for Mobile Agents via Step-Level Consequence Reasoning and Aggregation

arXiv:2608.20797v1 Announce Type: new Abstract: Evaluating language-guided mobile agents has recently shifted from rule-based to model-based approaches to achieve scalable and automated assessments. H

Bern2Edge: A Neurosymbolic Compiler for Edge Deployment via Bernstein Polynomial Networks

arXiv:2608.20497v1 Announce Type: new Abstract: Deploying high-accuracy neural networks on resource-constrained edge devices remains challenging, as existing approaches treat training, compression, an

researcharxiv-cs-lg

Beyond Imitation: Self-Improving Robot Policies via Off-Policy Q-Planning

arXiv:2608.21204v1 Announce Type: cross Abstract: Behaviour Cloning (BC) has driven remarkable progress in robot manipulation, yet it is fundamentally limited by its inability to self-improve: a polic

Calibrating Criterion Revision in LLM Agents: Failure Modes and a Trace-Anchored Protocol

arXiv:2608.20729v1 Announce Type: new Abstract: Language-model agents can improve after failure or carry text across episodes without revising what counts as success. We study the narrower attribution

local-aiarxiv-cs-ai

CAS: Conformalized Agentic Search via Adaptive Retrieval and Policy Weighting

arXiv:2608.20771v1 Announce Type: new Abstract: Search Agents face a severe reliability crisis during reinforcement learning (RL) fine-tuning. Heuristic Top-K retrieval often causes critical evidence

safetyarxiv-cs-ai

Crane: Context-Guided Prompt Learning and Attention Refinement for Zero-Shot Anomaly Detection

arXiv:2504.11055v3 Announce Type: replace Abstract: Zero-shot anomaly detection and localization aims to learn from source-domain data and generalize to unseen target domains without target-domain sam

local-aiarxiv-cs-cv

Decoupling Policy Extraction for Offline Reinforcement Learning

arXiv:2608.20909v1 Announce Type: new Abstract: Offline RL methods commonly jointly train the actor and critic, where the critic is used to guide the actor toward higher-value actions. This coupled le

safetyarxiv-cs-lg

Degree-Mass Message Passing for Betweenness Ranking in Directed and Undirected Networks

arXiv:2602.09716v2 Announce Type: replace Abstract: Computing the importance of nodes in networks is a long-standing fundamental problem that has driven extensive study of various centrality measures.

Delay-corrected Bellman operator + causal attribution for constrained RL contraction proof under unknown stochastic delay [R]

model-releasesr-machinelearning

Standard constrained RL assumes consequences are immediate and attributable to the current action. This breaks down whenever violations are delayed and stochastic, which is most real-world settings yo

DiGS-Avatar: Single-Image Animatable 3D Human Reconstruction via UV-Space Diffusion

arXiv:2608.20759v1 Announce Type: new Abstract: Single-image 3D human reconstruction often suffers from over-smoothed textures and geometric inconsistencies. While diffusion models improve generative

researcharxiv-cs-cv

Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect

arXiv:2510.12734v2 Announce Type: replace Abstract: Variable importance (VI) methods are often used for hypothesis generation, feature selection, and scientific validation. In the standard VI pipeline

researcharxiv-cs-lg

Empowering autonomous agents with advanced security governance

model-releasesgoogle-cloud-ai

AI agents are the ultimate insiders. We grant them permission to read emails, query databases, and trigger API calls. They don’t just retrieve information, they take action. Agents offer incredible po

Applications

Enhancing LLMs in Predictive Political QA with Semi-Structured Data

arXiv:2608.21218v1 Announce Type: new Abstract: Predictive political question answering (QA), such as predicting how a political actor will vote, goes beyond factual lookup. External political resourc

applicationsarxiv-cs-ai

ForeTime-VLA: Causal Future-Token Distillation from a World Action Model for Conveyor-Belt Manipulation

arXiv:2608.20735v1 Announce Type: new Abstract: Manipulating moving objects requires a policy to anticipate contact events, yet vision-language-action (VLA) policies are commonly fine-tuned from the c

safetyarxiv-cs-ai

Free-Text Evaluation of LLMs for 5G Domain Knowledge and Fault Analysis using LLM-as-Judge

arXiv:2608.21021v1 Announce Type: cross Abstract: Real-world fault analysis in 5G and emerging 6G networks demands domain expertise to analyze free-text diagnostics, including root-cause explanations

Future Dynamic 3D Reconstruction: Toward 3D World Modeling with Disentangled Ego-Motion

arXiv:2606.18250v2 Announce Type: replace Abstract: Forecasting the evolution of dynamic environments is crucial for autonomous agents. While generative world models have achieved high photorealism in

agentsarxiv-cs-cv

Fuzzy-MoE: Interpretable Regime-Conditioned Expert Routing for Non-Stationary Multivariate Time Series Forecasting

arXiv:2608.20761v1 Announce Type: cross Abstract: In non-stationary multivariate time series, different variables and samples often exhibit heterogeneous latent dynamic states, while existing deep for

Generating Multi-view Adversarial Examples for Visual Geometry Grounded Transformer

arXiv:2608.20748v1 Announce Type: new Abstract: The Visual Geometry Grounded Transformer (VGGT) enables unified feed-forward 3D reconstruction from multi-view images. However, deploying such a high-pe

safetyarxiv-cs-cv

Identify, Locate, Link: End-to-End Key-Value Extraction from Document Images

model-releasesarxiv-cs-cl

arXiv:2608.20868v1 Announce Type: cross Abstract: Document processing pipelines traditionally cascade optical character recognition (OCR) engines with downstream models for structured information extr

Identity-Aware Human-Object Interaction Motion Captioning

arXiv:2608.20690v1 Announce Type: cross Abstract: Existing human-object interaction (HOI) motion captioning methods typically describe what happens while referring to the subject using generic terms s

InfinityEdit: Infinite Video Editing with a Lightweight Edit-Ignition Adapter

arXiv:2608.20910v1 Announce Type: new Abstract: With large pretrained models, existing methods have effectively improved instruction-based video editing. However, most of them rely on an in-place edit

researcharxiv-cs-cv

Interesting new approach to enable memory in long-running agents. Weighted Memory Tree organizes execution into tasks, subtasks, and actions…

Interesting new approach to enable memory in long-running agents. Weighted Memory Tree organizes execution into tasks, subtasks, and actions, then gives every memory a retention score that moves. Even

model-releasesdair-ai--x

Industry

Introducing new Ray capabilities on SageMaker HyperPod

Amazon SageMaker HyperPod now offers managed Ray support on Amazon EKS. Create and monitor Ray clusters, connect JupyterLab and Code Editor notebooks to live clusters, get out-of-the-box observability

industryaws-ml-blog

InverFill: One-Step Inversion for Enhanced Few-Step Diffusion Inpainting

arXiv:2603.23463v2 Announce Type: replace-cross Abstract: Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-

researcharxiv-cs-ai

Llama-Mobile: Efficient 2.7-Bit Quantization of VLMs

model-releasesarxiv-cs-cv

arXiv:2608.21134v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) on mobile devices is challenging due to their significant memory and compute requirements. We present a framewor

Logic-VLA: A Temporal Logic Conditioned Vision-Language-Action Model

arXiv:2608.20556v1 Announce Type: new Abstract: Vision-language-action (VLA) models can follow natural-language (NL) task instructions, but such instructions may not precisely specify safety-critical

safetyarxiv-cs-ro

Masking Is Not Enough: Generative Restoration for Multimodal De-Identification in Medical AI

arXiv:2608.21133v1 Announce Type: new Abstract: Medical image-text data can expose protected health information (PHI) through both visible image content as well as accompanying text, creating a barrie

researcharxiv-cs-cv

MedRAGChecker: Claim-Level Verification for Biomedical Retrieval-Augmented Generation

arXiv:2601.06519v2 Announce Type: replace Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupport

safetyarxiv-cs-cl

MobileMoE - a facebook Collection

model-releasesr-localllama

MobileMoE is a family of on-device Mixture-of-Experts (MoE) language models with sub-billion active parameters, designed to push the quality–efficiency Pareto frontier for on-device LLMs, including th

My AI broadly agrees with Arvind's AI: state-level data center bans have very little impact overall on AI progress. If your concern is AI de…

My AI broadly agrees with Arvind's AI: state-level data center bans have very little impact overall on AI progress. If your concern is AI development, concentration of power, future use, or anything e

safetyethan-mollick--x