Knowledge catalogue
arXiv:2606.27973v1 Announce Type: cross Abstract: Speech-based cognitive impairment detection offers a noninvasive, accessible alternative to costly biomarker assays, yet transformer-based models rema
arXiv:2606.28011v1 Announce Type: cross Abstract: We propose an agentic Large Language Model (LLM) framework for active Fault-Tolerant Control (FTC) that transforms fault detection outputs into constr
arXiv:2606.27679v1 Announce Type: cross Abstract: Probe-based uncertainty estimation (UE) has emerged as a prominent approach to detect hallucinations in Large Language Models (LLMs) by learning uncer
FULL INTERVIEW: Engineers Edward Coristine (@as400495) and Tai Groot (@taigrr) just released an ML model called Rampart for the National Design Studio. It's a local-first, open-source AI privacy model
arXiv:2601.18197v2 Announce Type: replace Abstract: While Large Vision-Language Models (LVLMs) have significantly advanced GUI agents' capabilities in parsing textual instructions, interpreting screen
Google Cloud Japan ブログにインタビュー記事を掲載いただきました。 「Sakana Fugu」のサービス基盤として、GoogleのEnterprise Agent Platformを全面採用した経緯について、プロジェクトを率いたチーフサイエンティストのYujin Tangをはじめ、3名のサイエンティストが開発の舞台裏を語っています。 「Sakana Fugu はスポーツに例えるな
Lauren Forristal / TechCrunch: Google says the Gemini app now offers personalized Nano Banana image generation, previously limited to Plus, Pro, and Ultra users, to eligible US users for free — Google
arXiv:2606.28235v1 Announce Type: cross Abstract: Autonomous coding agents now open and merge pull requests in shared repositories at scale, and the field evaluates them the way it has always evaluate
arXiv:2606.27413v1 Announce Type: cross Abstract: Understanding which genes control which traits in an organism remains one of the central challenges in biology. Despite significant advances in data c
arXiv:2606.27917v1 Announce Type: new Abstract: Contextual bandits with graph-structured arms arise in recommendation, citation retrieval, and social advertising, where arms connected on a graph tend
arXiv:2606.28215v1 Announce Type: cross Abstract: Extracting dynamic 4D object interactions from massive, in-the-wild monocular videos offers a highly efficient data collection pathway for scaling Emb
arXiv:2601.17642v2 Announce Type: replace Abstract: Safety alignment in Large Language Models is critical for healthcare; however, reliance on binary refusal boundaries often results in over-refusal o
arXiv:2606.27999v1 Announce Type: new Abstract: Despite the rapid advance of Multimodal Large Language Models (MLLMs) in high-level video understanding, a fundamental bottleneck remains: these models
arXiv:2511.03217v2 Announce Type: replace-cross Abstract: Large language models (LLMs) excel in generating fluent utterances but can lack reliable grounding in verified information. At the same time,
arXiv:2511.07836v4 Announce Type: replace-cross Abstract: The curse of dimensionality remains a persistent challenge in modern optimization problems. Expanding the search space into higher dimensions
arXiv:2409.13007v3 Announce Type: replace-cross Abstract: Class imbalance poses a significant challenge in classification tasks, often causing standard learning algorithms to become biased toward the
In the next version of Claude Code: subagents run in the background by default, so you can keep talking to Claude while your subagents work If you want your agent to run in the foreground, just tell C
Jyoti Mann / The Information: Internal documents: Meta is placing strict limits on how engineers in its applied AI division can use Claude Code and Codex, fearing inadvertent distillation — As Meta Pl
Introducing Cloak: Use Claude or ChatGPT without your personal data ever leaving your machine. Two 3B models do the on-device PII cloaking: praxis-spanfinder-3b and praxis-relevance-3b. They swap your
ComfyUI announced June product launches featuring desktop application improvements, MCP (Model Context Protocol) enhancements, and core engine upgrades during a live demonstration with audience Q&A se
arXiv:2606.27595v1 Announce Type: new Abstract: Web-agent benchmarks overwhelmingly measure depth -- pinning one obscure answer behind a chain of constraints -- while breadth, exhaustively enumerating
A new proposal would ban the sale of Americans' health and location information to data brokers - including information people reveal to an AI chatbot like ChatGPT or Claude. In the coming weeks, Sena
arXiv:2606.27448v1 Announce Type: new Abstract: This paper studies the problem of regret minimization in Markovian bandits with non-observable states and possibly constrained decision epochs. The focu
arXiv:2510.19119v2 Announce Type: replace Abstract: In networked environments, it is common for users to share recommendations about content, products, services, and possible courses of action. Whethe
arXiv:2602.10238v2 Announce Type: replace Abstract: The growing size of Large Language Models (LLMs) makes efficient inference challenging, primarily due to the memory demands of the autoregressive Ke
arXiv:2606.28182v1 Announce Type: cross Abstract: Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years. However, existing l
arXiv:2606.27871v1 Announce Type: new Abstract: Vision Language Models (VLMs) have emerged in the robotic domain as a powerful tool that enables environmental perception with language context, serving
arXiv:2606.16494v2 Announce Type: replace-cross Abstract: Knowledge-based visual question answering (KB-VQA) lets vision-language systems answer questions that exceed their parametric knowledge by con
This OpenAI publication analyzes employment opportunities and workforce transitions related to artificial intelligence development and deployment across Europe. It likely examines which sectors and re
arXiv:2606.27537v1 Announce Type: new Abstract: Video generation models aspire to simulate dynamic environments, and several benchmarks now evaluate memory consistency across frames. However, most ass
arXiv:2606.27687v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, classify, and annotate data whose outputs feed downstream hypothesis tests. However, L
arXiv:2606.28027v1 Announce Type: cross Abstract: Neural video codecs have surpassed classical codecs in coding efficiency but remain impractical for deployment due to cross-platform incompatibility a
arXiv:2602.05233v2 Announce Type: replace Abstract: Vision-language-action models have advanced robotic manipulation but remain constrained by reliance on the large, teleoperation-collected datasets d
arXiv:2606.28144v1 Announce Type: new Abstract: Reconstructing high-fidelity, relightable 3D avatars from a single in-the-wild image is a challenging ill-posed problem, primarily hindered by the scarc
arXiv:2402.11736v3 Announce Type: replace Abstract: Kernel herding belongs to a family of deterministic quadratures that seek to minimize the maximum mean discrepancy (MMD), that is, the worst-case in
arXiv:2606.27895v1 Announce Type: cross Abstract: Differentiable partial differential equation (PDE) solvers underpin solver-in-the-loop ML training, gradient-based optimal control, and inverse proble
Most popular model on @OpenRouter (10tr tokens) turns out to be a 1.6tr MoE by @Meituan_LongCat (superapp/DoorDash of China) Basically Gemini / Opus 4.6 level 35tr tokens trained entirely on 50k Chine
arXiv:2606.28057v1 Announce Type: cross Abstract: Language models (LMs) represent tokens using embedding matrices that scale linearly with the vocabulary size. To constrain the parameter footprint, pr
arXiv:2606.16682v3 Announce Type: replace-cross Abstract: When AI agents use language models to evaluate their own outputs in a feedback loop, systematic biases emerge. We show that Evaluator Preferen
arXiv:2606.27660v1 Announce Type: new Abstract: Vision-Language Models (VLMs) improve generalization and interpretability in autonomous driving but suffer from efficiency issues due to long visual tok
arXiv:2606.27826v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly deployed as embodied planners in egocentric environments, where task success requires not only
arXiv:2606.27412v1 Announce Type: cross Abstract: 3D Scene Graph Generation (3DSGG) represents 3D scenes as structured object-relation-object graphs, providing a compact relational abstraction for spa
Showcasing the importance of open source innovation in American AI, Palantir’s new intelligent engine — introduced today — uses NVIDIA Nemotron open models to serve the needs of U.S. government agenci
arXiv:2606.27459v1 Announce Type: new Abstract: We consider the cubic nonlinear Schrodinger (NLS) equation on two-dimensional flat tori with varying aspect ratios. In this formulation, the choice of a
Ornith-1.0: Self-Scaffolding LLMs for Agentic Coding This is an interesting new open weights (MIT licensed) model, the first model release from DeepReinforce. [...] with variants including 9B Dense, 3
arXiv:2606.27880v1 Announce Type: new Abstract: Unified fashion generation integrates tasks like virtual try-on and garment reconstruction into a single model to reduce task-specific adaptation costs.
arXiv:2606.27785v1 Announce Type: cross Abstract: Training-free compression methods for large language models (LLMs) often use calibration data to guide compression decisions. ROCKET, a recent method
In this post, we show how pairing Amazon Nova 2 Lite with Anthropic’s Claude Sonnet 4.6 delivers an efficient solution for digitizing scanned documents at scale. We built a two-model pipeline on Amazo
arXiv:2606.28252v1 Announce Type: cross Abstract: Early detection of oral cancer markedly improves clinical outcomes, yet specialized diagnostic tools remain scarce in low-resource settings. Smartphon
arXiv:2606.28274v1 Announce Type: cross Abstract: Accurate network traffic prediction is a critical element for efficient resource allocation in dynamic urban cellular networks. However, prediction re
arXiv:2606.27821v1 Announce Type: cross Abstract: Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting re
arXiv:2606.27578v1 Announce Type: cross Abstract: Reward models for Reinforcement Learning from Human Feedback (RLHF) pool preferences across thousands of annotators and fit one global affine calibrat
arXiv:2606.28322v1 Announce Type: new Abstract: We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness
arXiv:2606.27793v1 Announce Type: cross Abstract: Long-context language models suffer from position bias, where information in middle positions is underutilized. Attention Sorting addresses this by it
arXiv:2606.27449v1 Announce Type: new Abstract: Multi-head attention conventionally partitions the hidden dimension equally across all heads at every layer, enforcing an identical representational sub
arXiv:2603.19466v2 Announce Type: replace Abstract: Effective collaboration begins with knowing when to ask for help. For example, when trying to identify an occluded object, a human would ask someone
arXiv:2509.03704v2 Announce Type: replace Abstract: Cooperative perception through Vehicle-to-Everything (V2X) communication offers significant potential for enhancing vehicle perception by mitigating
arXiv:2606.27608v1 Announce Type: new Abstract: We present Qwen-Image-2.0-RL, a post-training pipeline that applies reinforcement learning from human feedback (RLHF) and on-policy distillation (OPD) t
arXiv:2606.27385v1 Announce Type: cross Abstract: The most widely used RANSAC variants score candidate models by counting inliers or summing per-point scores that saturate beyond a residual threshold.
arXiv:2502.16886v4 Announce Type: replace-cross Abstract: To reduce memory consumption during LLM inference, a handful of methods have been proposed for KV cache pruning. While these techniques can ac