Knowledge catalogue
arXiv:2607.03869v1 Announce Type: cross Abstract: Referring remote sensing image segmentation isolates the object named by a natural-language expression in an aerial image. Existing training-free meth
arXiv:2607.03862v1 Announce Type: new Abstract: AI-generated images have proliferated rapidly, motivating extensive research. Most existing AI-generated image detectors are developed and evaluated und
arXiv:2607.02518v1 Announce Type: cross Abstract: OpenClaw requests are dominated by long, tool-augmented prefixes, including system prompts, conversation history, and tool outputs fed back into the c
arXiv:2512.16357v3 Announce Type: replace Abstract: Pre-trained Latent Diffusion Models (LDMs) have recently shown strong perceptual priors for low-level vision tasks, making them a promising directio
Moving Beyond the Prototype The AI landscape has shifted. While 'vibe coding' with tools like Antigravity and AI Studio lets you build and deploy complex agents in minutes, the real work begins on 'Da
arXiv:2607.04103v1 Announce Type: cross Abstract: The release of SR 26-2 marks a significant modernization of U.S. model risk management by replacing SR 11-7 with a more risk-based and materiality-sen
arXiv:2607.04147v1 Announce Type: cross Abstract: Automated fine-grained perception of calligraphy styles--a task vital to cultural heritage preservation--remains a critical challenge for Large Vision
arXiv:2607.04241v1 Announce Type: cross Abstract: Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible
arXiv:2607.03449v1 Announce Type: cross Abstract: Current Vision-Language-Action (VLA) models excel at robotic manipulation but often struggle with non-Markovian tasks requiring long-term memory and r
arXiv:2607.05017v1 Announce Type: cross Abstract: The performance of deep learning models crucially depends on the settings of hyperparameters like learning rate, initialization scale, and weight deca
arXiv:2607.04675v1 Announce Type: new Abstract: This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Gra
If you care about AI, and want a nuanced view, you should watch this. I promise it will be worth your time. An excellent video from the @WorldSciFest featuring @GaryMarcus , in which he discusses—amon
arXiv:2607.02542v1 Announce Type: new Abstract: General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actio
arXiv:2607.05389v1 Announce Type: new Abstract: Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assump
arXiv:2607.02560v1 Announce Type: new Abstract: Pedestrian-level wind prediction is essential for urban design and wind-comfort assessment, but high-fidelity simulations such as LES remain computation
arXiv:2607.04988v1 Announce Type: new Abstract: Unified models for robot manipulation aim to equip one policy with both the semantic priors of pretrained VLMs and the physical dynamics learned through
arXiv:2607.05393v1 Announce Type: cross Abstract: Time-domain surveys generate many transient candidates, making Real-Bogus classification a critical step in automated discovery pipelines. Reliable la
arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina
arXiv:2607.03696v1 Announce Type: new Abstract: Existing Salient Object Detection in Optical Remote Sensing Image (ORSI-SOD) methods mainly adopt the static inference strategy, which uses fixed traine
arXiv:2607.03991v1 Announce Type: cross Abstract: Repeated LLM calls are the standard way to estimate how trustworthy a Text-to-SQL result is: run the pipeline multiple times, judge each SQL execution
arXiv:2412.13533v4 Announce Type: replace Abstract: Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown prom
arXiv:2401.10805v4 Announce Type: replace-cross Abstract: We introduce the novel concept of visually Connecting Actions and Their Effects (CATE) in video understanding. CATE can have applications in a
arXiv:2607.03715v1 Announce Type: new Abstract: Medical imaging models often degrade when deployed at new clinical sites due to differences in imaging equipment, protocols, and patient populations. Te
arXiv:2607.02715v1 Announce Type: new Abstract: Recently, neural operators have shown promising outcomes for learning solution operators of differential equations directly from data. This framework le
arXiv:2607.04579v1 Announce Type: cross Abstract: CI/CD workflows have become executable operational policy: they decide what gets built, tested, released, and deployed, and they mediate how maintaine
arXiv:2607.04774v1 Announce Type: new Abstract: Untargeted tandem mass spectrometry (MS/MS) detects thousands of small molecules per biological sample, yet most go unidentified because they are absent
arXiv:2606.16337v3 Announce Type: replace Abstract: Predictive modeling for clinical decision support requires not only strong predictive performance but also transparent decision logic. Although deep
arXiv:2607.04930v1 Announce Type: cross Abstract: In the pursuit of robust and generalizable category-level object pose estimation, most existing methods adopt parametric formulations that learn effec
// MetaSkill-Evolve // Great paper on self-improving agents. Most self-improving agents rewrite what the agent does and leave how it improves frozen and hand-authored. That improvement procedure never
Recent breakthroughs in instruction-based image editing have captured significant attention, as models are now capable of handling real-world editing demands with the practicality required by everyday
arXiv:2510.01764v3 Announce Type: replace Abstract: Reinforcement learning (RL) research requires diverse, challenging environments that are both tractable and scalable. While modern video games may o
Axios: OpenAI says GPT-5.6 Sol, along with Terra and Luna, will launch publicly on Thursday; a source says the US Department of Commerce cleared a broad rollout — The U.S. Department of Commerce has g
arXiv:2601.07376v2 Announce Type: replace Abstract: We introduce extsc{OpenTinker}, an open infrastructure for training large language model (LLM) agents with many LoRA-backed policies over shared exe
arXiv:2602.14401v2 Announce Type: replace-cross Abstract: Vision-Language Navigation VLN requires large-scale trajectory instruction data from private indoor environments, raising significant privacy
arXiv:2601.16064v2 Announce Type: replace-cross Abstract: Deep learning has substantially advanced medical image segmentation, yet achieving robust generalization across diverse imaging modalities and
arXiv:2607.04782v1 Announce Type: cross Abstract: Many real-world games do not admit a fixed, compact rule set: instead, their dynamics are defined by interactions among a large and often evolving col
arXiv:2607.03732v1 Announce Type: new Abstract: Precise control over complex dynamics remains challenging for modern video generative models, as text prompts alone often cannot specify physically plau
arXiv:2508.08983v2 Announce Type: replace-cross Abstract: Humans can learn a new manipulation task from one or two demonstrations and then perform it in a new room, with new objects, under new constra
arXiv:2607.03515v1 Announce Type: cross Abstract: In many machine learning applications, the most relevant items for a query should be efficiently retrieved. The relevance function is usually an expen
arXiv:2607.03680v1 Announce Type: cross Abstract: Recent AI-generated text detection work often introduces a new benchmark together with a specialized detector tailored to it. We revisit this practice
arXiv:2607.03960v1 Announce Type: new Abstract: Achieving simultaneous preference alignment and distillation acceleration in video diffusion models remains an open challenge. Existing methods optimize
arXiv:2508.11657v2 Announce Type: replace-cross Abstract: Objective: Sparse Bayesian learning provides an effective framework to solve high-dimensional problems in brain signal decoding. However, conv
arXiv:2511.15706v3 Announce Type: replace Abstract: Dense feature matching aims to estimate all correspondences between two images of a 3D scene and has recently been established as the gold standard
arXiv:2607.02781v1 Announce Type: cross Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates.
arXiv:2607.05259v1 Announce Type: new Abstract: Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and
arXiv:2511.17812v3 Announce Type: replace-cross Abstract: Flow matching models effectively represent complex distributions, yet estimating expectations of functions of their outputs remains challengin
arXiv:2208.00657v2 Announce Type: cross Abstract: Building detection and change detection using remote sensing images can help urban and rescue planning. Moreover, they can be used for building damage
arXiv:2607.03091v1 Announce Type: new Abstract: Silicon sampling-using large language models (LLMs) to simulate human survey respondents-has emerged as a promising approach for augmenting traditional
arXiv:2510.09458v2 Announce Type: replace-cross Abstract: Interest in forestry automation is growing alongside rapid advances in deep learning. In particular, tree detection and taxonomic classificati
arXiv:2607.04591v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation by integrating visual perception, language understan
arXiv:2607.03451v1 Announce Type: cross Abstract: While skill optimization for autonomous agents has gained traction, existing methods rely on complex pipelines. This leaves a fundamental question una
arXiv:2607.04764v1 Announce Type: cross Abstract: Visual Place Recognition (VPR) in lifelong deployment requires continuous adaptation to new environments without catastrophic forgetting. In this pape
arXiv:2511.09072v2 Announce Type: replace-cross Abstract: Traditional Visual Odometry (VO) and Visual Inertial Odometry (VIO) methods rely on a 'pose-centric' paradigm, which computes absolute camera
arXiv:2607.02814v1 Announce Type: cross Abstract: Personal agents will increasingly negotiate on behalf of users: splitting costs with other personal agents, appealing platform decisions, escalating s
arXiv:2603.10002v2 Announce Type: replace-cross Abstract: We consider the task of end-to-end spreadsheet generation, where language models produce spreadsheet artifacts to satisfy users' explicit and
arXiv:2607.03329v1 Announce Type: new Abstract: Conventional uniform convergence bounds and empirical risk minimization break down in massive over-parameterized models, such as large language transfor
arXiv:2607.03089v1 Announce Type: cross Abstract: HAR is increasingly expected to run continuously on edge devices, yet recent LLM-based methods remain hard to deploy: raw sensor prompts are long, clo
arXiv:2603.08982v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) have become a leading backbone for video generation, yet their quadratic attention cost remains a major bottleneck. Sp
arXiv:2607.03572v1 Announce Type: cross Abstract: Knowledge distillation is usually framed as a choice of what to match in the teacher - its logits, hidden features, or sample relations - which presup
arXiv:2607.04232v1 Announce Type: cross Abstract: Unlike natural-language specifications, executable formal specifications provide machine-checkable constraints for verifying, debugging, and repairing