AI News · Models & Methods
Computer vision news: image recognition, multimodal models, detection and visual understanding.
293 stories · Updated
293 stories
Concept bottleneck models route predictions through human-understandable concepts, making their intermediate states inspectable and editable. Extending this model family to forecasting requires modeling how concept activations evolve over time as objects, actions, and their interactions change, yet existing CBMs…
Frozen visual encoders make prototype heads competitive in few-shot class-incremental learning (FSCIL), but it remains unclear how much of the residual head gap is sensitive to noisy novel-class means rather than to the subsequent changes introduced by classifier refitting. On identical features, we construct a…
World models predict how scenes evolve, but they are difficult to interrogate: given a model that forecasts a video, one cannot easily ask what would have happened had a particular interaction between two objects been different. We present Factorized Object Relations for Counterfactual Editing (FORCE), a world model…
Test-time adaptation (TTA) enables vision--language models such as CLIP to adapt to distribution shifts without labels or access to source data. Existing methods adapt through feature caching, prototype estimation, or the online accumulation of feature statistics, but most ultimately score a test feature against a…
Deaf inclusion across sub-Saharan society faces regional hurdles, with Nigeria as the core empirical focus. Existing recognition models demand heavy computational infrastructure. However, standard mobile phones used locally rarely exceed 1 GB to 4 GB of RAM. This study addresses constraints through a lightweight…
Selective prediction allows a model to abstain on uncertain inputs, but a single confidence threshold can disproportionately reject examples from particular groups. We study how confidence scores produce this imbalance in frozen vision-language models (OpenAI CLIP, LAION CLIP, SigLIP). We express a family of scores…
Diffusion transformers have achieved remarkable success in image generation, but accelerating attention while preserving generation quality remains a major challenge at high resolutions. Inspired by statistical physics and the widespread occurrence of scale-free laws in nature, we introduce Scale-Free Attention (SFA)…
Pathology workflows require multiple visual judgments about the same slide, from identifying tumor type to assessing grade and invasion. Generating and parsing a separate textual response for each structured question adds latency between visual evidence and usable decisions. Building on the System One paradigm, we…
While frontier coding agents can generate high-quality 3D scenes and articulated assets, they struggle to create coherent long-horizon animations. When equipped with general-purpose harnesses, they frequently produce physically implausible outputs, generating objects that interpenetrate, lack physical support, or move…
The reasoning capabilities of vision-language models (VLMs) can be limited by incomplete or inaccurate visual observations in the general domain. In unmanned aerial vehicle (UAV) scenes, small targets, subtle attributes, and changing viewpoints further complicate perception and understanding. Therefore, we introduce…