Search: “benchmark”

OmniWeaving: Towards Unified Video Generation with Free-form Composition and Reasoning

arXiv:2603.24458v3 Announce Type: replace Abstract: While proprietary systems such as Seedance-2.0 have achieved remarkable success in omni-capable video generation, the academic research community la

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Model Releases

On-Policy Self-Distillation for Multi-Turn Image Editing

DGX agent

arXiv:2609.35611v1 Announce Type: new Abstract: Instruction-based image editing has achieved strong performance in single-turn settings, yet practical editing is often iterative, with each instruction

model-releasesarxiv-cs-cv

29 Sept 2026

On the Pitfalls of Verbalized Confidence Priors for Calibrating Large Reasoning Models

arXiv:2609.32470v1 Announce Type: new Abstract: Large reasoning models (LRMs) often suffer from overconfidence when expressing their uncertainty. Confidence-aware reinforcement learning (RL) offers a

safetyarxiv-cs-lg

One Perception, All Maneuvers: Directional Traffic Signal Understanding for Maneuver-Level Signal Intent Prediction

arXiv:2609.32316v1 Announce Type: new Abstract: Traffic lights are a key regulatory signal for autonomous driving at urban intersections, yet existing traffic signal perception is still predominantly

One Sensor, Whole Body - 3D Body Pose from a Single Consumer Earbud IMU

arXiv:2609.34978v1 Announce Type: new Abstract: Consumer earbuds already stream inertial motion data from the head, one of the most widely worn sensor locations on the body. We ask how much of the 3D

OneCanvas: 3D Scene Understanding via Panoramic Reprojection

arXiv:2606.19253v2 Announce Type: replace Abstract: Existing approaches to 3D scene understanding in Vision-Language Models (VLMs) either rely on complex, model-specific geometry encoders or large tra

OPERA: A Unified Omnimodal Progressive Spatio-Temporal Reasoning Agent for Referring Video Segmentation

arXiv:2609.33338v1 Announce Type: new Abstract: Referring video segmentation with heterogeneous multimodal queries---spanning text, audio, and reference images---demands both robust cross-modal unders

agentsarxiv-cs-cv

Optimal Nonparametric Dynamic Pricing with Censored Demand and Adversarial Inventory

arXiv:2609.32949v1 Announce Type: new Abstract: We study online dynamic pricing with censored demand, where an arbitrary inventory level is revealed before pricing and may adapt to past observations,

Parameter-Efficient 3D Segmentation of Liver and Liver tumors: Depthwise factorization Scales Better Than Dense Convolution with Spatial Dimensionality

arXiv:2609.33077v1 Announce Type: new Abstract: Three-dimensional dense convolutional networks are the strongest performers on volumetric medical image segmentation, but their parameter counts scale p

PARSEE-VAD: Efficient Training-Free Online Video Anomaly Detection via Proposition-Aware Reasoning and Streaming Evidence Escalation

arXiv:2609.33236v1 Announce Type: new Abstract: Training-free online video anomaly detection (VAD) with frozen multimodal language models faces two coupled challenges: extracting reliable current-wind

safetyarxiv-cs-cv

Pay for Hints, Not Answers: LLM Shepherding for Cost-Efficient Inference

arXiv:2601.22132v2 Announce Type: replace Abstract: Large Language Models (LLMs) deliver state-of-the-art performance on complex reasoning tasks, but their inference costs limit deployment at scale. S

PGL-3D: Towards Progressive Geometric Learning for 3D Visual Query Localization

arXiv:2609.33558v1 Announce Type: new Abstract: 3D Visual Query Localization (3DVQL) retrieves the latest contiguous occurrence of a queried object in an RGB--point-cloud sequence and predicts a 9-DoF

Physics-Attested Federated Learning: Securing Collaborative Anomaly Detection in Critical Water Infrastructure

arXiv:2609.34804v1 Announce Type: cross Abstract: Federated learning enables industrial operators to train shared intrusion detection models without disclosing proprietary operational telemetry. Howev

PINNMorph: Evolving Online Adaptation Policies for Physics-Informed Neural Networks

arXiv:2609.32685v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training beha

safetyarxiv-cs-lg

PIVOT: Pivot-Aware On Policy Self Distillation for Multi-Turn VLM Agents

arXiv:2609.35303v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) via Group-Relative Policy Optimization (GRPO) is widely used for multi-turn VLM agent training, ye

Applications

PolyStepOR: Learning to Decide Without Optimal Decisions

arXiv:2609.32465v1 Announce Type: new Abstract: Decision-focused learning (DFL) trains predictors for downstream decision quality, but often relies on optimal reference decisions that are expensive to

applicationsarxiv-cs-lg

PReCache: Efficient KV Cache Sharing for Multi-LoRA Agents via Low-Rank Precomputation and Neutral Reconstruction

arXiv:2609.34054v1 Announce Type: new Abstract: Multi-LoRA agent systems enable efficient role specialization by sharing a common backbone model. However, each agent repeatedly processes the growing s

agentsarxiv-cs-lg

Prediction Limits and Koopman Closure of Geometry-Induced Soft State Abstractions

arXiv:2609.32652v1 Announce Type: cross Abstract: We study when geometry-induced soft state abstractions admit accurate finite-dimensional linear dynamics. Each state is represented by simplex-valued

Presence Is Not Faithfulness: Figurative Vehicle Intrusion in Text-to-Image Generation

arXiv:2609.32188v1 Announce Type: new Abstract: Text-to-image (TTI) models increasingly generate high-quality images from natural-language prompts, yet figurative language exposes a failure: a vehicle

Privacy-Preserving Full-Body Meshing from mmWave Radar via Mesh Foundation Model Supervision

arXiv:2609.34768v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) radar enables privacy-preserving human perception, but the extreme sparsity of point clouds from commercial single-chip senso

Probabilistic Geodesic Flow Matching on Location-Scale Families

arXiv:2609.34613v1 Announce Type: cross Abstract: Flow matching (FM) has recently emerged as a promising framework for generative modeling due to its conceptual simplicity and strong empirical perform

Probe to Act: Elevating Browser-Use Agent via Active Visual Probing

arXiv:2609.33646v1 Announce Type: cross Abstract: Browser-use agents require seamless alignment between structured web metadata and visual information, while preserving relevant context across long in

Program-Verified Self-Evolution for Vision-Language Models

arXiv:2609.33855v1 Announce Type: new Abstract: Self-evolving vision-language models train on questions they generate from unlabeled images. Since these questions have no gold answers, prior methods l

Progressive-View On-Policy Distillation for Regional-to-Global Transfer in Multimodal LLMs

arXiv:2609.32333v1 Announce Type: new Abstract: Regional-to-global distillation uses crop-conditioned guidance to improve full-image understanding. The challenge is to effectively transfer the teacher

safetyarxiv-cs-cv

Local Ai

PULSE: Identifying Demonstration-Utility Features with Sparse Autoencoders

arXiv:2609.32469v1 Announce Type: cross Abstract: In-context learning is highly sensitive to demonstration choice, yet most methods select demonstrations using external query-demonstration similarity.

local-aiarxiv-cs-lg

Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

arXiv:2509.22161v4 Announce Type: replace Abstract: Vector quantization, which discretizes a continuous vector space into a finite set of representative vectors (a codebook), has been widely adopted i

Q-learning Penalized Transformer for Safe Offline Reinforcement Learning

arXiv:2609.34426v1 Announce Type: new Abstract: This paper addresses the problem of safe offline reinforcement learning, which involves training a policy to satisfy safety constraints using an offline

Q-WAM: 4-Bit Quantization of World Action Models with Action-Subspace Protection

arXiv:2609.33269v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly generate video and robot actions through iterative diffusion and perform strongly in robotic manipulation. However,

Tutorials

QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities

arXiv:2609.34842v1 Announce Type: new Abstract: Existing multimodal time series foundation models (TSFMs) typically model heterogeneous modalities through largely shared mechanisms, overlooking the di

tutorialsarxiv-cs-lg

Quality Determines Direction, Length Shapes Magnitude: Length Control for Open-Ended Reinforcement Learning

arXiv:2609.34718v1 Announce Type: new Abstract: Reinforcement learning (RL) changes not only what language models say, but also how much they say, often increasing response length at the cost of token

Quantifying the Effect of Test Set Contamination on Generative Evaluations

arXiv:2601.04301v3 Announce Type: replace Abstract: As frontier AI systems are pretrained on web-scale data, test set contamination has become a critical concern for accurately assessing their capabil

Quasi Linear Kernel Attention with Infinite Capacity

arXiv:2609.35349v1 Announce Type: new Abstract: The evaluation cost of transformers with softmax attention scales quadratically with sequence length. Kernel attention addresses this by replacing softm

Query, Align, and Distill: Navigation-Aware Cross-Modal Interaction for Efficient Vision-and-Language Navigation

arXiv:2609.33097v1 Announce Type: new Abstract: Recent large-scale Vision-and-Language Navigation (VLN) models deliver strong accuracy but remain costly to deploy due to their large parameter counts a

Query-aligned video frame selection for long video understanding

arXiv:2609.31668v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) process multimodal inputs by converting text, images, and videos into token sequences that are subsequently pro

safetyarxiv-cs-cv

QuPID: Quantum Parameter-Efficient Input-Dependent Retrieval Adaptation for Medical RAG

arXiv:2609.33351v1 Announce Type: cross Abstract: Fidelity-based quantum retrieval ranks candidates by the fidelity between query and archive states. Applying a shared input-independent unitary after

Rate-Distortion Adaptive Primitive Selection for Omnidirectional Gaussian Splatting

arXiv:2609.34367v1 Announce Type: new Abstract: Learned image codecs (LICs) achieve high reconstruction quality, but their decoding speed is often insufficient for immersive virtual reality (VR). Gaus

Readout is not Recovery: Dissociating Coordinate Emission from Visual-Corruption Repair in Vision-Language Models

arXiv:2609.32757v1 Announce Type: cross Abstract: VLM bounding-box localization is both language generation and spatial commitment. Parseable fields such as bbox_2d make localization easy to score, bu

Recent Advances in Agentic Agri-Robotic Phenotyping: A Perspective Review from Fragmented Multimodal Sensing to Unified PhenoAgent Intelligence

arXiv:2609.34567v1 Announce Type: new Abstract: This review examines the evolution of plant phenotyping from conventional manual trait measurement to high-throughput, robotic, and artificial intellige

agentsarxiv-cs-cv

ReGDiff: Guided Diffusion in Regulated Latent Space for Exploring Metamaterial Voxel Geometry

arXiv:2609.34231v1 Announce Type: new Abstract: Metamaterials are artificially engineered structures whose mechanical and physical behaviors are strongly shaped by geometry rather than composition. Vo

Reinforcement Learning to Initialize Newton-Raphson for AC Power Flow with Quantum Annealing-Based Environment Updates

arXiv:2511.20237v2 Announce Type: replace-cross Abstract: The Newton-Raphson (NR) method is widely used for solving power flow (PF) equations due to its quadratic convergence. However, its performance

agentsarxiv-cs-lg

Reliability-Gated Fusion of Consumer Head and Foot IMUs for Lower-Body 3D Pose

arXiv:2609.35764v1 Announce Type: new Abstract: Sparse inertial pose estimation promises camera-free motion capture from consumer devices, but consumer sensors are unreliable: firmware-fused orientati

REMEDY: How Far Is Video Generation from Medical Education World Models?

arXiv:2609.32460v1 Announce Type: new Abstract: Recent video generation models produce realistic videos and show potential as a foundation for world models. These advances create opportunities for gen

Representation Editing for Multimodal Test-Time Adaptation

arXiv:2609.32263v1 Announce Type: new Abstract: Multimodal test-time adaptation (TTA) aims to adapt a pretrained multimodal model online to distribution shift across modalities using unlabeled test da

safetyarxiv-cs-lg

Applications

Residual Diffusion Implicit Models

arXiv:2609.33020v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art results across multiple tasks. However, in inverse problems, standard initialization from pure Gaussian noise

applicationsarxiv-cs-cv

Local Ai

ResonAct: Streaming Metrics for Runtime Diagnosis and Self-Healing in Multi-Agent Systems

arXiv:2609.34701v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple specialized agents, external tools, and long-runni

local-aiarxiv-cs-lg

Local Ai

Resource-Aware Federated Mixture-of-Experts with Adaptive Pruning for Onboard Learning in LEO Satellite Constellations

arXiv:2609.31932v1 Announce Type: cross Abstract: Low-Earth-orbit (LEO) satellites are increasingly expected to perform onboard learning for applications such as disaster response and environmental mo

local-aiarxiv-cs-cv

ReSPO: Reshaped Sequence Policy Optimization for Gradient Starvation in Off-Policy Learning

arXiv:2609.35433v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) frequently reuses rollouts across multiple policy updates, increasing the mismatch between the cur

ReSync: Re-Aligning the Two Clocks of Asynchronous World-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.33944v1 Announce Type: new Abstract: Jointly generating future video and actions has become a standard recipe for world-action models, and the strongest systems denoise the two streams on s