Every story across every category, newest first. Each card links to the original publisher; daily-brief posts open as editorial pages.
arXiv:2607.01469v1 Announce Type: new Abstract: Agentic Video Question Answering (VideoQA) systems invoke tools during inference, but their tool libraries are fixed, so recurring procedures are rebuilt…
arXiv:2607.02490v1 Announce Type: cross Abstract: Large vision-language models can reason over multimodal inputs by generating textual chains of thought (CoT). A key capability exhibited in CoT…
arXiv:2607.01437v1 Announce Type: new Abstract: Egocentric gaze estimation is commonly studied using models that process the full video with access to future frames, while real-world applications…
arXiv:2607.01938v1 Announce Type: cross Abstract: Manipulating fast and dynamically moving targets in unstructured 3D environments remains challenging for embodied AI. Existing visual-language-action models and world models…
arXiv:2607.01435v1 Announce Type: new Abstract: Significant advancement of immersive technologies such as Virtual and Augmented Reality (VR/AR) and their integration into diverse aspects of modern life…
arXiv:2604.03497v2 Announce Type: replace-cross Abstract: Vision-language-model (VLM)-guided reinforcement learning (RL) has recently attracted significant attention for it, replacing brittle hand-crafted rewards with semantically grounded signals; however,…
arXiv:2607.01312v1 Announce Type: new Abstract: Visual narratives are central to storyboards, comics, children's media, and film previsualization, where viewers understand stories from images alone. Recent generators…
arXiv:2607.01353v1 Announce Type: new Abstract: Video-based person re-identification (Re-ID) aims to retrieve the same identity in the query video clips from the gallery video clips. To…
arXiv:2607.01370v1 Announce Type: new Abstract: High definition map generation is essential for autonomous driving, yet remains a labor-intensive process at scale. We present MapDreamer, a generative…
arXiv:2607.01395v1 Announce Type: new Abstract: At the heart of human visual perception lies the ability to maintain a continuous and coherent understanding of the external world.…
arXiv:2607.01383v1 Announce Type: new Abstract: Multi-subject personalized image generation requires the precise rendering of all requested reference identities and their specified interactions based on a guiding…
arXiv:2607.01416v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide an intrinsically interpretable alternative to post-hoc explanations. However, existing CBMs often rely on predefined concept vocabularies…
arXiv:2607.01396v1 Announce Type: new Abstract: Urban expansion threatens global biodiversity, especially affecting arboreal species due to the fragmentation of forest habitats. The movement of arboreal species…
arXiv:2407.04277v2 Announce Type: replace Abstract: Pedestrian detection in conventional frame-based imaging often suffers from limited temporal responsiveness and substantial data redundancy. Inspired by the biological retina,…
arXiv:2603.12937v2 Announce Type: replace Abstract: Establishing accurate point-to-point correspondences between non-rigid 3D shapes remains a critical challenge, particularly under non-isometric deformations and topological noise. Existing functional…
arXiv:2512.03042v3 Announce Type: replace Abstract: We introduce PPTArena, a benchmark for PowerPoint editing that evaluates how agents modify real slides from natural-language instructions. Unlike benchmarks that…
arXiv:2606.25842v2 Announce Type: replace Abstract: Existing multi-modal large language models (MLLMs) face significant challenges in processing long video sequences due to strict input token limitations. As…
arXiv:2604.26283v4 Announce Type: replace Abstract: High-precision medical diagnosis relies not only on static imaging features but also on the implicit diagnostic memory experts instantly invoke during…
arXiv:2607.00736v2 Announce Type: replace Abstract: Self-Supervised Monocular Depth Estimation (MDE) has garnered attention in recent years due to its independence from ground truth. However, most existing…
arXiv:2510.09517v2 Announce Type: replace Abstract: Despite rapid advances in large language models (LLMs), statistical reasoning remains underrepresented in existing LLM benchmarks, which often do not reflect…
arXiv:2607.01431v1 Announce Type: new Abstract: We introduce ISOSCI, a benchmark of isomorphic cross-domain science problem pairs that separates reasoning ability from domain knowledge retrieval in LLM…
arXiv:2607.02510v1 Announce Type: cross Abstract: Despite alignment training, LLMs remain prone to generating unsafe outputs at deployment time. Monitoring outputs online and raising an alarm when…
arXiv:2607.01420v1 Announce Type: new Abstract: As grounded QA systems are increasingly deployed in AI assistants, accurately attributing generated answers to evidence is critical for user trust…
arXiv:2607.02266v1 Announce Type: cross Abstract: Most data-mixing methods assume the corpus has already been partitioned into groups, and the choice of those groups determines what a…