Knowledge catalogue
arXiv:2604.11632v1 Announce Type: new Abstract: We introduce CARTBENCH, a museum-grounded benchmark for evaluating vision-language models (VLMs) on Chinese artworks beyond short-form recognition and Q
arXiv:2604.10900v1 Announce Type: new Abstract: In large language models performing long-form reasoning, the KV cache grows rapidly with decode length, creating bottlenecks in memory and inference sta
arXiv:2510.05125v2 Announce Type: replace Abstract: While collaborative filtering delivers predictive accuracy and efficiency, and Large Language Models (LLMs) enable expressive and generalizable reas
arXiv:2602.02409v2 Announce Type: replace Abstract: Out-of-distribution (OOD) detection is critical for the safe deployment of deep neural networks. State-of-the-art post-hoc methods typically derive
Catch Or Dagan, AI21's Chief Product & Strategy Officer, at #AIDev26 on April 29: 'An End to Manual Tinkering: Optimizing Accuracy, Cost & Latency in Real-World Agents'. We'll be at Booth 121. See you
arXiv:2604.11087v1 Announce Type: new Abstract: Despite the groundbreaking advancements made by large language models (LLMs), hallucination remains a critical bottleneck for their deployment in high-s
arXiv:2603.09145v2 Announce Type: replace-cross Abstract: Current expansion-based methods for Class Incremental Learning (CIL) effectively mitigate catastrophic forgetting by freezing old features. Ho
arXiv:2604.11097v1 Announce Type: new Abstract: Monocular depth estimation is a fundamental yet challenging task in computer vision, especially under complex conditions such as textureless surfaces, t
arXiv:2604.10973v1 Announce Type: new Abstract: Reasoning over tabular data is a crucial capability for tasks like question answering and fact verification, as it requires models to comprehend both fr
arXiv:2604.10502v1 Announce Type: new Abstract: Content moderation in online platforms faces persistent challenges due to the evolving complexity of user-generated content and the limitations of tradi
arXiv:2503.21380v3 Announce Type: replace Abstract: The rapid advancement of large reasoning models has saturated existing math benchmarks, underscoring the urgent need for more challenging evaluation
arXiv:2604.09611v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in applications forming multi-request workflows like document summarization, search-based copilots,
arXiv:2509.00891v3 Announce Type: replace Abstract: Real-world adoption of closed-loop insulin delivery systems (CLIDS) in type 1 diabetes remains low, driven not by technical failure, but by diverse
arXiv:2509.22830v3 Announce Type: replace Abstract: The growing deployment of large language model (LLM) based agents that interact with external environments has created new attack surfaces for adver
arXiv:2604.10825v1 Announce Type: new Abstract: We introduce CheeseBench, a benchmark that evaluates large language models (LLMs) on nine classical behavioral neuroscience paradigms (Morris water maze
arXiv:2602.03108v3 Announce Type: replace Abstract: We introduce ChemPro, a progressive benchmark with 4100 natural language question-answer pairs in Chemistry, across 4 coherent sections of difficult
China leaps ahead of the US in the race to control dangerously anthropomorphic AI. 🚨 BREAKING: China's new law on AI anthropomorphism has been officially enacted, and it is the world's STRICTEST law o
arXiv:2509.20147v2 Announce Type: replace-cross Abstract: Consider N players and K games taking place simultaneously. Each of these games is modeled as a Tug-of-War (ToW) game where increasing the act
Google is launching a new Chrome workflow feature that allows you to reuse your favorite Gemini commands across multiple webpages. Any AI prompts can now be saved as 'Skills' in the Chrome desktop bro
arXiv:2604.09600v1 Announce Type: new Abstract: Temporal knowledge graph (TKG) reasoning aims to infer future facts at unseen timestamps from temporally evolving entities and relations. Despite recent
arXiv:2604.10114v1 Announce Type: cross Abstract: The generation of high-fidelity synthetic data is a cornerstone of modern machine learning, yet Large Language Models (LLMs) frequently suffer from ha
arXiv:2408.02786v4 Announce Type: replace Abstract: The realization of Urban Air Mobility (UAM) necessitates scalable global path planning algorithms capable of ensuring safe navigation within complex
arXiv:2602.18047v3 Announce Type: replace Abstract: City-scale person re-identification across distributed cameras must handle severe appearance changes from viewpoint, occlusion, and domain shift whi
arXiv:2604.09812v1 Announce Type: new Abstract: Recurrent claims present a major challenge for automated fact-checking systems designed to combat misinformation, especially in multilingual settings. W
arXiv:2601.14698v2 Announce Type: replace Abstract: Real-world fact-checking often involves verifying claims grounded in structured data at scale. Despite substantial progress in fact-verification ben
arXiv:2604.11320v1 Announce Type: new Abstract: Robot grasping of desktop object is widely used in intelligent manufacturing, logistics, and agriculture.Although vision-language models (VLMs) show str
arXiv:2604.10305v1 Announce Type: cross Abstract: Cooperative perception allows connected vehicles and roadside infrastructure to share sensor observations, creating a fused scene representation beyon
Claude Code Routines are here! In addition to a schedule, you can now trigger templated agents via GitHub event or API – with our infra & your MCP+repos They've changed how we do docs, backlog mainten
arXiv:2604.11251v1 Announce Type: new Abstract: Training language-conditioned whole-body controllers for humanoid robots requires large-scale datasets pairing motion trajectories with natural-language
ClawBench is a benchmark of 153 everyday web tasks spanning 144 live platforms across 15 categories — from completing purchases and booking appointments to submitting job applications. Unlike existing
arXiv:2604.11790v1 Announce Type: cross Abstract: Tool-augmented Large Language Model (LLM) agents have demonstrated impressive capabilities in automating complex, multi-step real-world tasks, yet rem
arXiv:2604.11784v1 Announce Type: cross Abstract: GUI agents drive applications through their visual interfaces instead of programmatic APIs, interacting with arbitrary software via taps, swipes, and
arXiv:2604.10352v1 Announce Type: new Abstract: Stateful tool-using LLM agents treat the context window as working memory, yet today's agent harnesses manage residency and durability as best-effort, c
arXiv:2604.11539v1 Announce Type: cross Abstract: Human perception of visual similarity is inherently adaptive and subjective, depending on the users' interests and focus. However, most image retrieva
Close your eyes and let the mind expand. Let no fear of death or darkness arrest its course. Allow the mind to merge with Mind. Let it flow out upon the great curve of consciousness. Let it soar on th
arXiv:2604.10032v1 Announce Type: cross Abstract: While modern generative models such as diffusion-based architectures have enabled impressive creative capabilities, they also raise important safety a
arXiv:2604.11801v1 Announce Type: new Abstract: With the recent progress of Large Language Models (LLMs), there is a growing interest in applying these models to solve complex and challenging problems
arXiv:2604.11201v1 Announce Type: cross Abstract: LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds a
arXiv:2604.10426v1 Announce Type: cross Abstract: Large Language Models (LLMs) struggle with knowledge-intensive tasks due to hallucinations and fragmented reasoning over dispersed information. While
arXiv:2604.10235v1 Announce Type: new Abstract: Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value
arXiv:2604.10496v1 Announce Type: new Abstract: Outliers have emerged as a fundamental bottleneck in preserving accuracy for low-precision large models, particularly within Mixture-of-Experts (MoE) ar
arXiv:2604.11641v1 Announce Type: cross Abstract: Code agents are advancing rapidly, but debugging them is becoming increasingly difficult. As frameworks orchestrate parallel tool calls and multi-stag
This r/ollama thread discusses using Ollama as a local model provider for OpenAI's Codex CLI, covering configuration and setup. Open models can be used with OpenAI's Codex CLI through Ollama, allowing
arXiv:2604.01687v2 Announce Type: replace Abstract: Anthropic proposes the concept of skills for LLM agents to tackle multi-step professional tasks that simple tool invocations cannot address. A tool
arXiv:2604.10584v1 Announce Type: new Abstract: Multispectral and Hyperspectral Image Fusion (MHIF) aims to reconstruct high-resolution images by integrating low-resolution hyperspectral images (LRHSI
arXiv:2604.10219v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved remarkable strides in visual reasoning through test time compute scaling, yet long chain reasoni
arXiv:2603.22479v3 Announce Type: replace-cross Abstract: Defining a constructive process to build general capabilities for language models in an automatic manner is considered an open problem in arti
arXiv:2604.11741v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown impressive capabilities in perceptual tasks, yet they degrade in complex multi-hop reasoning under multiplayer
arXiv:2509.19883v2 Announce Type: replace-cross Abstract: Singing Voice Synthesis (SVS) aims to generate expressive vocal performances from structured musical inputs such as lyrics and pitch sequences
A Reddit post from r/StableDiffusion showcasing community-generated comic-style images using Anima Preview 3, an intermediate checkpoint of a 2-billion-parameter text-to-image model developed through
Each year we compile our 10 Breakthrough Technologies list, featuring our educated predictions for which technologies will have the biggest impact on how we live and work. This year, however, we had a
arXiv:2604.10689v1 Announce Type: new Abstract: Recent developments have shown that Muon-type optimizers based on linear minimization oracles (LMOs) over non-Euclidean norm balls have the potential to
arXiv:2604.10037v1 Announce Type: cross Abstract: We present a metasurface imaging system capable of simultaneously capturing two images at close range (1-2~cm) and an additional image at long range (
arXiv:2604.10316v1 Announce Type: new Abstract: Background: Large Language Models (LLMs) are transforming artificial intelligence applications in healthcare due to their ability to understand, generat
arXiv:2604.09621v1 Announce Type: new Abstract: We present an agent-driven approach to the construction of parameter inference pipelines for scientific data analysis. Our method leverages a multi-agen
arXiv:2604.10875v1 Announce Type: cross Abstract: AI governance efforts increasingly rely on audit standards: agreed-upon practices for conducting audits. However, poorly designed standards can hide a
arXiv:2604.09836v1 Announce Type: new Abstract: AI agents hold growing promise for accelerating scientific discovery; yet, a lack of frontier evaluations hinders adoption into real workflows. Expert-w
arXiv:2604.11584v1 Announce Type: cross Abstract: We study computational aspects of a key problem in robust statistics -- the penalized least trimmed squares (LTS) regression problem, a robust estimat
arXiv:2604.10035v1 Announce Type: cross Abstract: In this study, we developed a computational implementation for a model of metaphor comprehension based on the theory of indeterminate natural transfor
arXiv:2604.10627v1 Announce Type: cross Abstract: How the brain supports language across different languages is a basic question in neuroscience and a useful test for multilingual artificial intellige