AI·The Economist explains bizarre anti-drone camouflage tactics used in Ukraine, including vivid black-and-white striped patterns on Russian lorries designed to confuse machine-vision systems on Ukrainian drones.
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AI·Developer created an interactive Jacobian-Lens visualizer and live steerer for GGUF models on llama.cpp, inspired by Anthropic's work and featuring a native GGUF server.
AI·2025 saw multiple AI companionship app closures including Woebot (150M users, clinical tool shut down due to unsustainable economics) and Dot AI (vision divergence, funds exhausted), with global closures in at least five products and domestic in eight; survivors like Replika (post-data deletion), Character.AI (Google talent acquisition), and China's Xin Bing (ice) lost users amid regulatory scrutiny and high inference costs, revealing unsustainable business models lacking self-reinforcing revenue.
AI·DeepSearch-World is a self-distillation framework for web search agents that uses self-generated experience for training in verifiable environments.
AI·Canvas360 is a two-stage in-context panoramic generation framework with geometry-aware pretraining and a 1M-sample dataset, supporting style transfer, inpainting, outpainting, and editing tasks.
AI·OpenCoF enables reasoning in video generation through temporal frame chains distinct from Chain-of-Thought, addressing training data gaps.
AI·SAM-MT extends Segment Anything 2 for real-time interactive multi-target video segmentation, improving FPS by jointly processing multiple targets instead of replicating single-target pipelines.
AI·Dual Latent Memory in Vision-Language-Action models for robotic manipulation interleaves historical experience fluidly in the native latent embedding space, overcoming Markovian limitations in long-horizon tasks.
AI·SWE-Review closes the loop on AI-generated pull requests by using an agentic reviewer that explores repositories, accepts or rejects PRs, and supplies structured revision feedback, outperforming one-shot generation on SWE-Review-Bench and enabling test-time scaling.
Accurate breast cancer classification from mammography requires effective integration of complementary information from craniocaudal (CC) and mediolateral oblique (MLO) views, which provide a more complete characterization of breast abnormalities. However, existing multi-view learning approaches typically rely on feature-level aggregation or single-stage cross-attention, which can entangle view-specific and shared representations and restrict interaction to limited network depths. To address th…
I understand that it may not be appropriate to call it “officially accepted” yet because of the wording used in the notification, and I also saw on Twitter/X that they said they are working on it. However, it has already been around three weeks since then, and we have already submitted the camera-ready version. Registration, visa applications, travel planning, and funding requests all depend on t…
Zero-Shot Compositional Action Recognition (ZS-CAR) requires recognizing novel verb-object combinations composed of previously observed primitives. In this work, we tackle a key failure mode: models predict verbs via object-driven shortcuts (i.e., relying on the labeled object class) rather than temporal evidence. We argue that sparse compositional supervision and verb-object learning asymmetry can promote object-driven shortcut learning. Our analysis with proposed diagnostic metrics shows that…
Touch supplies the physical grounding needed to perceive intrinsic material properties, such as friction and compliance, that vision alone often cannot resolve. Recent efforts for equipping multimodal LLMs with this tactile sense, however, expose a zero-sum trade-off: the limited parameter budget of compact models forces a choice between acquiring the new sensory modality and preserving the established vision-language reasoning. We present Splash, a mask-isolated tactile alignment learning fram…