AI & Machine Learning · Computer Science & AI
Computer Vision
The newest papers in Computer Vision that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 29 September 2026 to 5 November 2026: 4,996 arXiv preprints and 4 OpenAlex records.
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Newest papers, page 246
TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning
Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visual tokens.FedSocket: Recipient-Executable Knowledge Exchange for Heterogeneous Multimodal Federated Learning
Federated knowledge must remain usable by recipients with different modalities, private architectures, and tasks.When to Adapt: Multi-Signal Domain Shift Detection for Efficient Training-Free Adaptation in Open-Vocabulary Segmentation
Robust and reliable perception is essential for autonomous robots operating in real-world environments, particularly in long-term missions where environmental conditions may change significantly…TomoTransformer: Towards a Foundation Model for CT Reconstruction
Supervised deep learning has advanced sparse-view tomographic reconstruction.Procedural Core: A Compact Recurrent Initialization for Vision Transformers
Transformers are typically trained from random initialization, requiring all their capabilities to emerge from large-scale optimization.Targeted Visual Counterfactual Explanations for Contrastive Vision-Language Model
Current explanation methods for contrastive vision-language models such as CLIP mainly identify important regions without showing how to change the input in order to get a target prediction.VoxelSage: Tool-Augmented 3D CT Analysis and Simulator-Shielded Sequential Resection Planning for Liver Tumors
Preoperative liver-tumor assessment requires segmentation, physical-space measurement, visual evidence, and resection planning from the same three-dimensional CT volume.Texture Space Material Diffusion
We present a method for generating high quality materials for 3D objects entirely in texture space.Exemplar2VQA: A Scalable Exemplar-Driven Visual Question Answering Generation Framework via Multi-Agent Coding
Advancing spatial intelligence in Multimodal Large Language Models (MLLMs) is bottlenecked by the scarcity of complex, scalable 3D question-answer (QA) data.Tracing the Evidence: Faithful Token Attribution Through Vision-Language Reasoning
Large vision-language models (LVLMs) exhibit strong reasoning capabilities, yet the visual and textual evidence supporting the generated responses remains difficult to identify.Are In-Context Images Worth 10 Dimensions?
There has been significant work on understanding the In-Context Learning capabilities of Large Language Models, especially on the induction circuit.MeanFlowAdvantage: Stable Reward Fine-Tuning for Few-Step Average-Velocity Generators
MeanFlow enables efficient few-step generation by predicting interval-average velocities, but this representation creates a mismatch for reward fine-tuning: existing advantage-based objectives are…Med-RADIO: Reducing All Medical Domains Into One via Multi-Teacher Distillation
The rapid expansion of large-scale medical datasets and computational resources has driven significant progress in medical foundation models.PAIQ: Patch-Aligned Semantic Injection via Residual Rotation
Language-aligned and self-supervised visual encoders offer complementary strengths in semantic abstraction and spatial detail.Honeycomb: Constant-Size Scene Memory Representation for Video World Models
Video world models require persistent scene memory to maintain consistency during long-horizon video generation.VIF-Bench: Evaluating Visual Instruction Following in Multi-Reference Image Generation
Recent multimodal image generation models can take multiple images and textual instructions as input, enabling reference-based generation guided not only by text but also by visual instructions such…PolyOCR-Venus: Unified OCR Foundation Models for Text-Centric Visual Intelligence
Optical Character Recognition (OCR) is evolving from plain-text transcription toward general visual intelligence, requiring models to recognize, localize, and reason over textual information in…CogWAM: Aligning Semantic Cognition with World Action Modeling via Event-Driven Interfaces
Robot policies increasingly incorporate semantic reasoning and future-world prediction, yet combining these capabilities does not guarantee that local predictions and actions remain aligned with…The Camera Inside the Editor: Reading the Implicit Camera of Image Editors with Painted Calibration Patterns
Instruction-based image editors insert objects, restyle scenes and render new viewpoints, but it is unknown which camera they assume when they paint into a photograph.Multi-Site Real-World Performance of Commercial AI for Pulmonary and Incidental Pulmonary Embolism Detection
Pulmonary embolism (PE) is a leading cause of cardiovascular mortality, yet the real-world performance of FDA-cleared AI detection models remains incompletely characterized.