Knowledge catalogue
arXiv:2604.10551v1 Announce Type: new Abstract: This paper presents an overview of the NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models. This challenge utili
arXiv:2604.10159v1 Announce Type: new Abstract: The advancement of large language models (LLMs) has enhanced tabular question answering (Tabular QA), yet they struggle with open-domain queries exhibit
arXiv:2604.11523v1 Announce Type: new Abstract: We are entering an era in which individuals and organizations increasingly deploy dedicated AI agents that interact and collaborate with other agents. H
arXiv:2604.11004v1 Announce Type: cross Abstract: In this work, we introduce a new perspective on comparative image assessment by representing an image pair as a structured composition of its regions.
arXiv:2604.09791v1 Announce Type: new Abstract: Small language models are attractive for production deployment due to their low cost, fast inference, and ease of specialization. However, adapting them
arXiv:2604.11687v1 Announce Type: new Abstract: AI-generated text has become common in academic and professional writing, prompting research into detection methods. Less studied is the reverse: system
arXiv:2604.10397v1 Announce Type: cross Abstract: Video-based human-object interaction (HOI) understanding requires both detecting ongoing interactions and anticipating their future evolution. However
arXiv:2604.05489v3 Announce Type: replace Abstract: Text-to-Video (T2V) generation has benefited from recent advances in diffusion models, yet current systems still struggle under complex scenarios, w
arXiv:2512.12675v2 Announce Type: replace-cross Abstract: Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distingui
arXiv:2604.10609v1 Announce Type: new Abstract: Instance segmentation enables the analysis of spatial and temporal properties of cells in microscopy images by identifying the pixels belonging to each
arXiv:2604.09854v1 Announce Type: new Abstract: LLMs have so far failed both to generate consistently compelling stories and to recognize this failure--on the leading creative-writing benchmark (EQ-Be
arXiv:2604.11757v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landsc
arXiv:2509.20868v2 Announce Type: replace-cross Abstract: Structured reasoning can improve the inference performance of large language models (LLMs), but it also introduces computational cost and cont
arXiv:2604.11529v1 Announce Type: new Abstract: Foundation models have transformed natural language processing and computer vision, and a rapidly growing literature on time-series foundation models (T
arXiv:2604.09879v1 Announce Type: new Abstract: Deep neural networks for 3D point cloud understanding have achieved remarkable success in object classification and recognition, yet recent work shows t
arXiv:2604.10386v1 Announce Type: new Abstract: Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support earlier detection and improved care, but modeling su
arXiv:2604.10721v1 Announce Type: cross Abstract: Natural-language Guided Cross-view Geo-localization (NGCG) aims to retrieve geo-tagged satellite imagery using textual descriptions of ground scenes.
arXiv:2603.08715v2 Announce Type: replace-cross Abstract: Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between mod
arXiv:2604.10441v1 Announce Type: new Abstract: Medical large language models (LLMs) achieve impressive performance on standardized benchmarks, yet these evaluations fail to capture the complexity of
arXiv:2604.10990v1 Announce Type: cross Abstract: Scientific claim verification, the task of determining whether claims are entailed by scientific evidence, is fundamental to establishing discoveries
arXiv:2604.08595v1 Announce Type: cross Abstract: Existing evaluation methods for LLM-based AI systems, such as LLM-as-a-Judge, verdict systems, and NLI, do not always align well with human assessment
arXiv:2604.09210v1 Announce Type: new Abstract: Monocular imaging of animals inherently reduces 3D structures to 2D projections. Detection algorithms lead to 2D bounding boxes that lack information ab
arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com
arXiv:2604.08963v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) are increasingly deployed for complex workflows, their emergent properties-particularly the accumulation of bias-remai
arXiv:2604.08867v1 Announce Type: cross Abstract: Audio has rapidly become a primary interface for foundation models, powering real-time voice assistants. Ensuring safety in audio systems is inherentl
arXiv:2604.09155v1 Announce Type: cross Abstract: Graphical user interface (GUI) agents powered by vision language models (VLMs) are rapidly moving from passive assistance to autonomous operation. How
arXiv:2501.14377v2 Announce Type: replace Abstract: Autonomous drone racing has risen as a challenging robotic benchmark for testing the limits of learning, perception, planning, and control. Expert h
arXiv:2604.09535v1 Announce Type: new Abstract: Large foundation models have made significant advances in embodied intelligence, enabling synthesis and reasoning over egocentric input for household ta
EinsteinArena is an open-source benchmarking platform developed by Together AI designed to evaluate and rank AI models, with a live public leaderboard tracking model performance. The project welcomes
arXiv:2604.08931v1 Announce Type: new Abstract: Human cognitive development is shaped not only by individual effort but by structured social interaction, where role-based exchanges such as those betwe
Grok Grok-4.20 just took the #1 spot in the world for Medicine & Healthcare on Text Arena Grok is already saving lives by identifying critical conditions that human doctors miss. There have been many
arXiv:2603.19275v2 Announce Type: replace-cross Abstract: Automatic summarization of radiology reports is an essential application to reduce the burden on physicians. Previous studies have widely used
arXiv:2604.08559v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-wor
arXiv:2604.09338v1 Announce Type: new Abstract: Spatial reasoning is central to navigation and robotics, yet measuring model capabilities on these tasks remains difficult. Existing benchmarks evaluate
arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag
arXiv:2604.07956v2 Announce Type: replace Abstract: Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to
Ethan Mollick, a Wharton professor and prominent AI researcher, posted commentary on what appears to be a notable AI capability advancement, framing it as a predictable progression along established p
arXiv:2604.09415v1 Announce Type: cross Abstract: We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike exi
arXiv:2604.09521v1 Announce Type: cross Abstract: When two agents of different computational capacities interact with the same environment, they need not compress a common semantic alphabet differentl
arXiv:2604.09034v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has significantly impacted the field of natural language processing, but their growing complexity ra
arXiv:2604.09038v1 Announce Type: cross Abstract: Robust geo-localization in changing environmental conditions is critical for long-term aerial autonomy. While visual place recognition (VPR) models pe
arXiv:2604.08549v1 Announce Type: cross Abstract: We introduce VerifAI, an open-source expert system for biomedical question answering that integrates retrieval-augmented generation (RAG) with a novel
After seeing that Claude Mythos marketing turned out to be, as expected, a scam, I wanted to make a master list of tricks being used to market LLMs. The master list includes statements directly from l
Nous Research shared a post celebrating a model or benchmark achievement reaching the top of a performance leaderboard, likely referencing one of their Hermes or other open-source model releases. The
arXiv:2604.06327v1 Announce Type: cross Abstract: Recent diffusion-based text-to-speech (TTS) models achieve high naturalness and expressiveness, yet often suffer from speaker drift, a subtle, gradual
arXiv:2604.06696v1 Announce Type: new Abstract: The rapid development of AI agent systems is leading to an emerging Internet of Agents, where specialized agents operate across local devices, edge node
arXiv:2603.13354v3 Announce Type: replace-cross Abstract: Reliable crop disease detection requires models that perform consistently across diverse acquisition conditions, yet existing evaluations ofte
arXiv:2505.20662v3 Announce Type: replace Abstract: Efficient reproduction of research papers is pivotal to accelerating scientific progress. However, the increasing complexity of proposed methods oft
arXiv:2604.07763v1 Announce Type: new Abstract: As generative artificial intelligence evolves, deepfake attacks have escalated from single-modality manipulations to complex, multimodal threats. Existi
arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN
arXiv:2604.06216v1 Announce Type: cross Abstract: As LLM-powered chatbots are increasingly deployed in mental health services, detecting hallucinations and omissions has become critical for user safet
arXiv:2603.18472v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) perform strongly on natural images, yet their ability to understand discrete visual symbols remains u
arXiv:2601.08258v3 Announce Type: replace Abstract: Large language models increasingly fail in a way that scalar accuracy cannot diagnose: they produce a sound reasoning trace and then abandon it unde
arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac
arXiv:2602.11635v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved strong performance on perception-oriented tasks, yet their ability to perform mathematical sp
arXiv:2509.01986v4 Announce Type: replace-cross Abstract: In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While th
arXiv:2604.07772v1 Announce Type: new Abstract: Open-world video anomaly detection (OWVAD) aims to detect and explain abnormal events under different anomaly definitions, which is important for applic
arXiv:2511.15496v2 Announce Type: replace Abstract: Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. M
arXiv:2604.06793v1 Announce Type: cross Abstract: Software documentation is crucial for repository comprehension. While Large Language Models (LLMs) advance documentation generation from code snippets
arXiv:2412.19685v2 Announce Type: replace-cross Abstract: Existing facial forgery detection methods typically focus on binary classification or pixel-level localization, providing little semantic insi