Search: “framework”

Streaming-Aware Diffusion for Real-Time Video Super-Resolution via Cross-Step Attention

arXiv:2610.11746v1 Announce Type: new Abstract: Real-time video super-resolution requires high spatio-temporal fidelity under strict latency constraints, challenging diffusion models due to their iter

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

SV-TAD: Native Sparse Convs for Efficient Temporal Action Detection

DGX agent

arXiv:2610.11579v1 Announce Type: new Abstract: To adapt billion-parameter Vision Transformers for long-video understanding, recent methods freeze the backbone and train lightweight convolutional modu

model-releasesarxiv-cs-cv

9 Oct 2026

Syn-Omni: Structured Specialization and Progressive Collaboration for Omnimodal Embeddings

arXiv:2610.12256v1 Announce Type: cross Abstract: Omnimodal embeddings naturally involve both shared representations and modality-specific features across heterogeneous inputs. However, existing omnim

SynCo: Data Synthesis Co-Training for Self-Evolving LLMs via Multi-Agent Reinforcement Learning

arXiv:2610.11345v1 Announce Type: new Abstract: Self-evolving LLM agents promise to improve autonomously through continual interaction and learning, reducing their dependence on manually curated super

safetyarxiv-cs-ai

Synthesis Through Simulation: Generating Coherent Enterprise Data via Scalable Agent-System Interaction

arXiv:2610.10549v1 Announce Type: new Abstract: Tool-calling agents have become central to enterprise AI, yet training and evaluating them at scale remains severely constrained due to business and leg

safetyarxiv-cs-ai

TacHair: Tactile Contact-Distribution Guided Online Correction for Robotic Hair Stroking and Perception

arXiv:2610.10637v1 Announce Type: new Abstract: Hair stroking is common in daily grooming and personal care, and is also widely used in hair-product evaluation, motivating robots with similar physical

safetyarxiv-cs-ro

TAM: Task-Aware Memory Distillation for Efficient Spatiotemporal Prediction

arXiv:2610.11617v1 Announce Type: cross Abstract: Knowledge distillation enables efficient spatiotemporal prediction by transferring knowledge from an accurate teacher to a compact student. However, m

TAPNAV: Humanoid Navigation through Tactile Active Perception

arXiv:2610.10748v1 Announce Type: new Abstract: Navigation in vision-denied environments is challenging for humanoid robots because proprioceptive odometry drifts and localization uncertainty accumula

researcharxiv-cs-ro

Tell Robot What Not to Do: A Negation Understanding Perspective

model-releasesarxiv-cs-ro

arXiv:2610.11952v1 Announce Type: new Abstract: Instruction following enables robots to perform diverse tasks specified in natural language, making it a fundamental capability for human-robot interact

Temporal transformer CAN encoder with federated lightweight heads for anomaly detection

arXiv:2610.10613v1 Announce Type: new Abstract: Modern vehicles rely on large numbers of Electronic Control Units (ECUs) that constantly exchange information over the Controller Area Network (CAN) bus

TestJack: Should you trust the results in coding benchmarks? Agentic Coding Benchmarks Auditing via Evaluator Evolution

arXiv:2610.10619v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly reshaping software engineering, accompanied by an explosion of new code benchmarks. Yet nearly all exist

Local Ai

The '10th Juror': Open-Set Standpoint Screening for Bureaucratic Bias Detection

arXiv:2610.11136v1 Announce Type: new Abstract: Presupposing the boundaries of bias is itself a form of bias. We study closed-loop bias governance for Dutch government documents, where a system must d

local-aiarxiv-cs-cl

Towards Unified Evaluation of Prompt Enhancers for Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.11736v1 Announce Type: new Abstract: Modern video generators can realize increasingly complex visual narratives, positioning the prompt enhancer (PE) as a critical bridge from concise user

Transforming Image Editors into Video Editors

arXiv:2610.11037v1 Announce Type: new Abstract: Recent image editing systems have achieved impressive semantic understanding, visual fidelity, and instruction-following ability, while video editing re

Applications

Trust, Don't Trust, or Flip: Robust Preference-Based Reinforcement Learning with Multi-Expert Feedback

arXiv:2601.18751v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PBRL) offers a promising alternative to explicit reward engineering by learning from pairwise traject

applicationsarxiv-cs-ai

Universal Textual Teaching for LLMs

arXiv:2610.12114v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from stronger Teacher models to weaker Student models, but most methods require training the Student par

Tutorials

USDCraft: Geometrically Grounded Programmatic Modeling of Articulated 3D Assets for Simulation

arXiv:2610.11322v1 Announce Type: new Abstract: Geometrically faithful and functional articulated 3D assets are essential for real-to-sim robot manipulation, where policies trained in simulation must

tutorialsarxiv-cs-ro

V-CoLA: Vision Token Compression with Linear Attention

arXiv:2610.11251v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated impressive capabilities but suffer from substantial computational overhead, as vision tokens dominate th

Verification and Self-Improvement in Agentic AI: Foundations and Limits

arXiv:2610.10611v1 Announce Type: new Abstract: Agentic AI systems can improve by searching longer, receiving additional support, or modifying how they propose and verify outputs. A performance score

safetyarxiv-cs-ai

VersaCamVLA: Camera-Configurable VLA Policies for Robotic Manipulation

arXiv:2610.12451v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as powerful foundations for robotic manipulation, but their reliance on fixed camera configurations dur

VesselSDF: Distance Field Priors for Vascular Network Reconstruction

arXiv:2506.16556v2 Announce Type: replace-cross Abstract: Accurate segmentation of vascular networks from sparse CT scan slices remains a significant challenge in medical imaging, particularly due to

VICO: Visual Environments Co-Evolving for Vision-Language Model Reasoning

arXiv:2610.10782v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard recipe for post-training vision-language models (VLMs), but it typically a

VINCIE-NExT: Unlocking Video Editing from Images via In-Context Modeling

arXiv:2610.12104v1 Announce Type: cross Abstract: Building a capable video editor remains significantly harder than a video generator: editing requires (source, instruction, edited) triplets that are

Visible Reasoning Is Not a Universal Optimizer: Persona- and Thinking-Dependent Effects in Analytics Code Generation

arXiv:2610.10639v1 Announce Type: cross Abstract: Visible Chain-of-Thought (CoT) is often treated as a broadly useful reasoning instruction, yet analytics code generation combines natural-language amb

ViSkill: Reinforcing VLM Agents with Evolving Visual-Native Skills

arXiv:2610.12403v1 Announce Type: cross Abstract: Skill-augmented agents improve sample efficiency by distilling successful trajectories into reusable strategies. Yet most existing approaches remain t

safetyarxiv-cs-cl

WAM-Cache: Staleness-Bounded KV Reuse for Efficient World Action Models

arXiv:2610.11401v1 Announce Type: cross Abstract: World Action Models (WAMs) enable generalist robot manipulation by conditioning an action expert on representations from a pretrained video Diffusion

safetyarxiv-cs-cv

WAND: Learning Robust Navigation under Complex Wind Disturbances and Dense Obstacles for Quadrotors

arXiv:2610.11809v1 Announce Type: new Abstract: Robust navigation in cluttered environments remains a fundamental challenge for quadrotors, particularly when strong wind disturbances arise, which pert

safetyarxiv-cs-ro

When History Helps and Hurts: Selective History Use across Multimodal Turns

model-releasesarxiv-cs-cl

arXiv:2610.11948v1 Announce Type: new Abstract: Reliable multimodal interaction depends on selective use of conversational history: an earlier question may remain relevant while its previous answer is

When Lower Reconstruction Loss Hurts: Distributionally Robust Refinement for Low-Bit LLM Quantization

arXiv:2610.11226v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) relies heavily on reconstruction loss minimization to preserve model quality at low precision. We show that

World-Model Policy Arbiter for Goal-Conditioned Reinforcement Learning

arXiv:2610.10932v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) has produced a diverse set of goal-reaching algorithms, yet no single algorithm performs best acr

safetyarxiv-cs-lg

WorldAlign: Decoupled 4D Reward for World-Consistent Video Generation

arXiv:2610.12382v1 Announce Type: new Abstract: Faithful visual world simulation requires generated videos to maintain 4D world consistency, encompassing both static and dynamic consistency. Static co

safetyarxiv-cs-cv

YOCO: You Only Calibrate Once! Fast Mocap Calibration for Dexterous Teleoperation

arXiv:2610.11657v1 Announce Type: new Abstract: Dexterous teleoperation requires reliable human-hand state estimations. However, common low-cost motion-capture gloves and markerless trackers often exh

researcharxiv-cs-ro

A Geometry-Based Capacity Theory for Finite-Feature Associative Memory

arXiv:2610.09056v1 Announce Type: new Abstract: We develop a geometry-based capacity theory for exact-key retrieval in compressed finite-feature Hebbian associative memory. For random or approximately

A Self-Pruning Transformer: Extreme KV-Cache Compression with Universal Attention

arXiv:2610.09051v1 Announce Type: new Abstract: The large KV-cache size of modern LLMs creates a barrier to efficient deployment. Recent work has explored replacing attention layers' RoPE positional e

A Unified Kinematic Representation Enables Reusable Biological Joint Moment Estimation

arXiv:2610.09150v1 Announce Type: new Abstract: Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However

researcharxiv-cs-ro

Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation

arXiv:2610.08849v1 Announce Type: cross Abstract: Purpose: Current abdominal ultrasound (US) simulation methods often require CT-based anatomical references for ray-casting, limiting deformation and p

Hardware

Accelerating Floating-Point Satisfiability Solving via Gradient Normalization

arXiv:2610.08808v1 Announce Type: cross Abstract: Satisfiability Modulo Theories (SMT) solvers are foundational to software verification, program analysis, and compiler testing, particularly over the

hardwarearxiv-cs-lg

AdaPS-LiNGAM: Adaptive Predecessor Selection for Linear Non-Gaussian Acyclic Models under Small-Sample Settings

arXiv:2610.09782v1 Announce Type: new Abstract: Causal discovery becomes particularly challenging when the available sample size is small relative to the number of variables. This challenge also arise

Adaptive Risk-Certified Event-Triggered Replanning for Dynamic Navigation

model-releasesarxiv-cs-ro

arXiv:2610.09302v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires robots to plan under obstacle predictions whose errors are uncertain, non-stationary, and can induce ra

Adaptive Visual Token Reduction for Accelerated Image Understanding

arXiv:2610.09252v1 Announce Type: new Abstract: Large Vision-Language Models achieve strong VQA performance, but processing high-resolution, information-rich images requires substantial computation, m

AdSpark: A Large-Scale Dataset and Benchmark for Product-Centric Advertisement Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.10047v1 Announce Type: new Abstract: Product-centric advertisement video generation aims to create promotional videos that preserve fine-grained product identity while presenting selling po

Adversarial Images Hijack Web Agents from Visual Grounding to Browser Execution

model-releasesarxiv-cs-cl

arXiv:2610.09240v1 Announce Type: cross Abstract: Modern web agents built on large vision-language models process webpages, select relevant UI elements, and translate model outputs into browser action

Agentic RSR: Real-to-Sim-to-Real through Scene Reconstruction and Execution-Grounded Robot Policies

arXiv:2610.10479v1 Announce Type: cross Abstract: A simulation of a real robot workspace must preserve task-relevant interactions, while policies developed in it must operate on observations available

safetyarxiv-cs-cv

AirGroundVLN: A Large-Scale Benchmark for Goal-Oriented Air-Ground Collaborative Vision-and-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2610.10421v1 Announce Type: new Abstract: Goal-oriented Vision-and-Language Navigation (VLN) requires agents to locate and reach targets described in natural language without prescribed routes.

An AI-assisted conditioning and geological interpretation workflow for usage in implicit geological modeling

arXiv:2610.09871v1 Announce Type: cross Abstract: Implicit modeling and Relative Geologic Time are geological modeling techniques that enable more efficient, faster, less biased and more reproducible

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation

model-releasesarxiv-cs-cl

arXiv:2505.19912v3 Announce Type: replace Abstract: We present Adjacent Possible Exploration (APE), a selective fine-tuning method for adapting large language models that systematically explores param

Argos: Adapt Rich Geometric Priors for Generalizable Online Scene-Change-Detection

model-releasesarxiv-cs-cv

arXiv:2610.10181v1 Announce Type: new Abstract: Robots operating in dynamic environments require reliable detection of how their surroundings change over time. Existing learning-based methods largely

Ask the Expert: LLM-Guided Reinforcement Learning for Autonomous Cyber Defense

arXiv:2610.09337v1 Announce Type: cross Abstract: Policy-based reinforcement learning (RL) approaches have produced promising results for autonomous cyber defense; however, they are sample-inefficient

safetyarxiv-cs-lg