Knowledge catalogue
Politico: Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban — The Commerce Department's Ce
arXiv:2604.09594v1 Announce Type: new Abstract: Spatial competence is the quality of maintaining a consistent internal representation of an environment and using it to infer discrete structure and pla
arXiv:2505.17012v3 Announce Type: replace-cross Abstract: Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In thi
arXiv:2604.10152v1 Announce Type: new Abstract: The Mixture-of-Experts (MoE) architecture has emerged as a promising approach to mitigate the rising computational costs of large language models (LLMs)
arXiv:2604.09557v1 Announce Type: cross Abstract: Speculative Decoding (SD) has emerged as a critical technique for accelerating Large Language Model (LLM) inference. Unlike deterministic system optim
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:2604.09553v1 Announce Type: cross Abstract: LLM development has aroused great interest in Sequential Recommendation (SR) applications. However, comprehensive evaluation of SR models remains lack
arXiv:2604.04552v2 Announce Type: replace-cross Abstract: Ensemble methods are widely used to improve predictive performance, but their effectiveness often comes at the cost of increased memory usage
arXiv:2604.09737v1 Announce Type: cross Abstract: Structured prediction requires models to generate ontology-constrained labels, grounded evidence, and valid structure under ambiguity, label skew, and
arXiv:2604.10286v1 Announce Type: new Abstract: Autonomous language-model agents increasingly rely on installable skills and tools to complete user tasks. Static skill auditing can expose capability s
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:2604.10527v1 Announce Type: cross Abstract: Referring multi-object tracking (RMOT) is a task of associating all the objects in a video that semantically match with given textual queries or refer
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
Sub-32B open weights models now offer GPT-5 level intelligence with Qwen3.5 27B (Reasoning) matching GPT-5 (medium) at 42 and Gemma 4 31B (Reasoning) matching GPT-5 (low) at 39 on the Artificial Analy
arXiv:2511.17925v3 Announce Type: replace-cross Abstract: Recent advances in whole-body robot control have enabled humanoid and legged robots to perform increasingly agile and coordinated motions. How
arXiv:2604.03723v2 Announce Type: replace Abstract: Controlling both camera motion and object dynamics is essential for coherent and expressive video generation, yet current methods typically handle o
arXiv:2604.11563v1 Announce Type: cross Abstract: Providing AI agents with reliable long-term memory that does not hallucinate remains an open problem. Current approaches to memory for LLM agents -- s
arXiv:2604.11498v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) is challenging because visually similar actions differ by subtle spatio-temporal cues. Many recent systems
arXiv:2604.10727v1 Announce Type: cross Abstract: Classical information-theoretic generalization bounds typically control the generalization gap through KL-based mutual information and therefore rely
arXiv:2604.10720v1 Announce Type: new Abstract: Artificial models that simulate how learners act and respond within educational systems are a promising tool for evaluating tutoring strategies and feed
arXiv:2305.14299v3 Announce Type: replace-cross Abstract: Learning high quality sentence embeddings from dialogues has drawn increasing attentions as it is essential to solve a variety of dialogue-ori
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:2504.06313v5 Announce Type: replace Abstract: This paper investigates how popular text-to-image (T2I) models, DALL-E 3 and Gemini 3 Pro Preview, depict people from 206 nationalities when prompte
arXiv:2604.10261v1 Announce Type: new Abstract: Existing tool-use benchmarks for LLM agents are overwhelmingly linear: our analysis of six benchmarks shows 55 to 100% of instances are simple chains of
arXiv:2604.10577v1 Announce Type: cross Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automat
This r/ollama post describes a technique where an LLM is used to automatically tune its own llama.cpp runtime flags — such as parameters related to GPU offloading, KV cache quantization, batch sizes,
arXiv:2604.11364v1 Announce Type: new Abstract: The two most influential cognitive architecture frameworks for AI agents, CoALA [21] and JEPA [12], both lack an explicit Knowledge layer with its own p
arXiv:2604.10272v1 Announce Type: new Abstract: We prove that in a coupled Kuramoto oscillator network at stable equilibrium, the physical phase displacement under weak output nudging is the gradient
arXiv:2604.09911v1 Announce Type: cross Abstract: In the psychological literature the term `general intelligence' describes correlations between abilities and not simply the number of abilities. This
arXiv:2604.11309v1 Announce Type: cross Abstract: Large Language Models (LLMs) face prominent security risks from jailbreaking, a practice that manipulates models to bypass built-in security constrain
arXiv:2604.11284v1 Announce Type: cross Abstract: We present THEIA, a modular neural architecture that learns complete Kleene three-valued logic (K3) end-to-end without any external symbolic solver, a
There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to adapt to the future. Here’s the briefest state of the AI world
arXiv:2604.10135v1 Announce Type: cross Abstract: Researchers have explored different ways to improve large language models (LLMs)' capabilities via dummy token insertion in contexts. However, existin
arXiv:2510.15552v3 Announce Type: replace-cross Abstract: Large language models (LLMs) still struggle with multi-hop reasoning over knowledge-graphs (KGs), and we identify a previously overlooked stru
arXiv:2604.10511v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for causal and counterfactual reasoning, yet their reliability in real-world policy evaluation remain
This is why we released liteparse :) Free, open-source, designed for agents. Natively supports OCR / screenshotting for deeper visual understanding in a document when needed. @kepano I just tried it t
arXiv:2604.11465v1 Announce Type: new Abstract: Large language model (LLM) agents show promise on realistic tool-use tasks, but deploying capable agents on modest hardware remains challenging. We stud
arXiv:2604.11544v1 Announce Type: cross Abstract: Structured memory representations such as knowledge graphs are central to autonomous agents and other long-lived systems. However, most existing appro
arXiv:2604.10291v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown promising performance in time series modeling tasks, but do they truly understand time series data? While multip
arXiv:2604.09658v1 Announce Type: cross Abstract: Gaze gestures can provide hands free input on mobile devices, but practical use requires (i) gestures users can learn and recall and (ii) recognition
Today we're launching a rebuilt version of Claude Code on desktop. The app has been redesigned for the ground up to make it easier than ever to parallelize work with Claude. I haven't opened an IDE or
arXiv:2604.09613v1 Announce Type: cross Abstract: Production vLLM fleets provision every instance for worst-case context length, wasting 4-8x concurrency on the 80-95% of requests that are short and s
arXiv:2604.10733v1 Announce Type: cross Abstract: Large language models increasingly serve as conversational agents that adopt personas and role-play characters at user request. This capability, while
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:2604.10784v1 Announce Type: new Abstract: Recent advances in unified multimodal models (UMMs) have led to a proliferation of architectures capable of understanding, generating, and editing acros
arXiv:2604.09625v1 Announce Type: new Abstract: We study whether large-scale unlabelled web data and LLM-based synthetic annotations can improve multilingual hate speech detection. Starting from texts
arXiv:2604.10009v1 Announce Type: cross Abstract: Automatic sleep staging is a multimodal learning problem involving heterogeneous physiological signals such as EEG and EOG, which often suffer from do
arXiv:2604.10480v1 Announce Type: new Abstract: Post-training data plays a pivotal role in shaping the capabilities of Large Language Models (LLMs), yet datasets are often treated as isolated artifact
arXiv:2604.10980v1 Announce Type: new Abstract: Diffusion models have become the de facto standard for modern visual generation, including well-established frameworks such as latent diffusion and flow
arXiv:2604.09850v1 Announce Type: new Abstract: Existing text-to-image diffusion models, while excelling at subject synthesis, exhibit a persistent foreground bias that treats the background as a pass
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:2604.10999v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on many multimodal benchmarks. However, the ability to follow complex visual paths -- a task that human o
arXiv:2604.10110v1 Announce Type: new Abstract: Large Language Models (LLMs) have become a key foundation for enabling personalized smart home experiences. While existing studies have explored how sma
OpenAI is expanding trusted access to its AI models for cybersecurity purposes, enabling vetted researchers, defenders, and organizations to leverage advanced AI capabilities for cyber defense applica
arXiv:2602.14200v4 Announce Type: replace Abstract: Time Series Language Models (TSLMs) are emerging as unified models for reasoning over continuous signals in natural language. However, long-context
arXiv:2604.09571v1 Announce Type: cross Abstract: Recent advances in vision-language models (VLMs) have sparked growing interest in using them to automate web tasks, yet their feasibility as independe
arXiv:2604.09574v1 Announce Type: new Abstract: The rise of autonomous GUI agents has triggered adversarial countermeasures from digital platforms, yet existing research prioritizes utility and robust
Google has launched **Skills in Chrome**, a feature that lets users save and reuse their most helpful Gemini AI prompts and run them with a single click. When a useful prompt is written in Gemini, it
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.
Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any frontier model selection. Till now we have mostly focused on