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Computer Vision
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The newest 5,000 papers, from 29 September 2026 to 5 November 2026: 4,999 arXiv preprints and 1 OpenAlex record.
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Newest papers, page 173
Harness Compilation: Which Decisions Should a Small Vision-Language Model Keep?
Small vision-language models may be able to read external evidence yet struggle to obtain it.MiniVer-V: Identifying Minimal Sufficient Evidence for Short Video Verification
A core challenge in short-video fact-checking is identifying which evidence is sufficient to support a verification conclusion.Breaking the Group Size Barrier: Parameter-Efficient Group Dance Generation with Chain-of-Dancers
Group dance generation aims to synthesize coordinated multi-dancer choreography from music, with broad applications in animation and interactive content creation.Attributing HOW, Not Just WHICH: Counterfactual Response Trajectories for Diffusion Models
Diffusion models have achieved remarkable success in image generation, yet tracing their outputs to individual training examples remains challenging.TAP3D: Thermal-Assisted 3D Human Point Clouds
Human body point clouds are a versatile representation for AI-enabled human sensing.V-CoLA: Vision Token Compression with Linear Attention
Vision-language models (VLMs) have demonstrated impressive capabilities but suffer from substantial computational overhead, as vision tokens dominate the input sequence.LR-V2X: Loss-Resilient Collaborative Perception under Low-Bandwidth Communication
Given the inherent unpredictability of packet loss in vehicular wireless communications, V2X collaborative perception can yield practical benefits only if agents can achieve reliable collaboration…Being-M0.7: A Latent World-Action Model for Humanoid Robots
Humanoid loco-manipulation requires coordinated locomotion and manipulation informed by future scene evolution and whole-body motion, yet learning these capabilities is constrained by scarce robot…When Scene Text Hijacks the Scene: Uncovering, Exploiting, and Mitigating Rendered-Text Semantic Leakage in Image Generation Models
The reliability and accountability of image generative models (IGMs) are essential for building responsible and trustworthy AI systems.Spatial-Frequency-Aware Implicit Neural Representation of Multidimensional Signals via MLP-KAN Fusion
Implicit Neural Representations (INRs) have emerged as a compelling paradigm for modeling multidimensional signals by mapping continuous coordinates to signal values.iCATS: Fast Video Generation via Interaction-Aware Sparse Attention and Timestep-Adaptive Sparsity
Training-free sparse attention offers a practical acceleration solution to Diffusion Transformers (DiTs) via reducing computations without fine-tuning.Efficient Multi-Granularity Knowledge Transfer for Radiology Report Generation
Radiology report generation can automatically generate clinical descriptions from X-ray images, thereby significantly improving the efficiency of radiologists.Collaboratively Guided Adversarial Robust Distillation with Teacher-Favorable Examples
Adversarial distillation transfers robustness from high-capacity teachers to compact students.FloorSAV: Elucidating Spatial Audio-Visual Context with 2D Floormap for AV-LLMs
While 3D spatial reasoning in dynamic egocentric environments is crucial for embodied intelligence, audio-visual large language models (AV-LLMs) lack explicit mechanisms to process and internalize…Deflating the Hessian: Rank-4 W4A4 Quantization for Multimodal Diffusion Transformers
In diffusion transformers, low-rank branches can mitigate 4-bit weight--activation (W4A4) post-training quantization (PTQ) loss by decomposing each weight into a low-bit residual and a…It's Always 10:10: Reference Images Break a Bias That Prompts Only Dent
Text-to-image models appear to reproduce the habits of the photographs they learned from.PathLang: A Language-Centered Benchmark for Vision-Language Models in Computational Pathology
Pathology vision-language models (VLMs) have shown strong visual perception ability, but their robustness in the language domain remains poorly characterized.Point-Focused Attention Meets Context-Scan State Space: Robust Biological Visual Perception for Point Cloud Representation
Synergistically capturing intricate local structures and global contextual dependencies has become a critical challenge in point cloud representation learning.EgoPhys: Estimating Peak Contact Force and Mechanical Work from Egocentric Manipulation Video
Physically grounded manipulation of articulated objects requires understanding both the maximum forces encountered during contact and the work performed as their parts move.Adaptive Adversarial Augmentation for Controllable Face Synthesis
Synthetic data provides a scalable alternative to real-world datasets for training face recognition models, particularly under challenging conditions such as low resolution, occlusion, and masks.