Knowledge catalogue
arXiv:2608.07062v1 Announce Type: new Abstract: Test-time adaptation (TTA) has become a practical way to adapt deployed models to unlabeled target data, a setting that is especially relevant in comput
arXiv:2608.07437v1 Announce Type: new Abstract: Reliable hypothesis testing is the foundation of many empirical scientific claims. Large language model (LLM) agents are increasingly used to automate t
arXiv:2608.07291v1 Announce Type: new Abstract: Foundation models have shown strong transferability in cardiac MRI (CMR), but their effectiveness for heterogeneous multi-view and multi-sequence CMR an
arXiv:2608.07294v1 Announce Type: cross Abstract: Generating mixed-type tabular data requires jointly modeling diverse feature distributions and their complex cross-column dependencies. Variational fl
arXiv:2608.07091v1 Announce Type: cross Abstract: Edge Artificial Intelligence (Edge AI) enables the deployment of AI models directly on local edge devices, while such deployments are subject to stric
arXiv:2608.07092v1 Announce Type: cross Abstract: Stochastic cortical self-reconstruction (SCSR) enables personalized mapping of gray matter atrophy, a hallmark of neurodegenerative disorders such as
arXiv:2602.02276v2 Announce Type: replace-cross Abstract: We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint op
arXiv:2608.07057v1 Announce Type: new Abstract: Knife-enabled violence presents a major public safety challenge, and law enforcement agencies require scalable tools for catalogue-level knife identific
arXiv:2608.06963v1 Announce Type: new Abstract: Biologically plausible learning models aim to explain how neural circuits can implement effective learning under the constraints of real neurons. Althou
arXiv:2608.06424v1 Announce Type: cross Abstract: Speech recordings often contain missing, corrupted, or incorrect regions that must be reconstructed or modified without re-synthesizing the entire utt
arXiv:2608.06378v1 Announce Type: cross Abstract: Driver emotions can affect risk perception, decision-making, and vehicle control under complex road conditions. Existing studies mainly focus on drive
I've been building a personal project and wanted to check with the community on multi-modal inputs since I can't find a lot of material around this online. Ultimately I'm trying to build something tha
arXiv:2608.07167v1 Announce Type: new Abstract: Giving an AI agent the ability to send emails, query databases, or execute commands is useful--until the agent is tricked into doing something it should
arXiv:2608.07395v1 Announce Type: cross Abstract: Large Language Model (LLM)-based automated algorithm design typically evolves algorithms as complete, indivisible programs. While this whole-program p
arXiv:2608.07367v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly used as a primary source of information and advice, understanding their alignment to humans in terms of
arXiv:2608.07126v1 Announce Type: cross Abstract: Most CubeSats, small and low-cost satellites roughly the size of a shoebox, do not survive as long as they were designed to: a study of 178 missions f
arXiv:2608.06690v1 Announce Type: cross Abstract: Most language-model access controls regulate behavior while leaving the same computation available to every request. We study a different systems ques
arXiv:2608.06896v1 Announce Type: new Abstract: Deep learning has achieved great success in recent years thanks to the availability of high-quality, well-annotated training data. However, this require
arXiv:2608.06917v1 Announce Type: new Abstract: Recent Large Multimodal Models (LMMs) have achieved impressive performance in recipe generation from food images.However, cooking is a structured transf
arXiv:2608.07435v1 Announce Type: cross Abstract: Vision-language models (VLMs) are improving rapidly, but benchmark development lags behind, making weaknesses hard to identify. Building stress tests
Thomas Barrabi / New York Post: Sources: officials say OpenAI risks its White House relationship by hiring Dean Ball, who has criticized Trump's AI strategy after leaving the administration — Top Open
arXiv:2608.07106v1 Announce Type: new Abstract: Deploying three-dimensional deep learning frameworks to low-power embedded processors is bottlenecked by the unstructured nature of spatial data and the
arXiv:2608.06672v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a robust architecture for grounding large language models (LLMs) in trusted knowledge. However, standard
arXiv:2608.07446v1 Announce Type: cross Abstract: Rapid adoption of large language models (LLMs) in enterprise settings has introduced operational, security, and governance risks. As generative AI app
arXiv:2608.06503v1 Announce Type: new Abstract: Recurrent context compression controls context growth in long-horizon agents, but its behavioral effects remain poorly understood. In this preliminary e
arXiv:2608.06657v1 Announce Type: new Abstract: Modern cyber-physical and AI-assisted systems couple human operators, AI decision modules, and automated controllers in a single control loop, so trustw
arXiv:2608.07371v1 Announce Type: cross Abstract: Recent agentic reinforcement learning methods use hindsight to complement sparse outcome rewards. However, a completed rollout can yield many such sig
arXiv:2608.07267v1 Announce Type: new Abstract: Recent vision-language navigation (VLN) systems increasingly adapt pretrained vision-language models (VLMs) into vision-language-action (VLA) policies t
arXiv:2608.06416v1 Announce Type: cross Abstract: Watermarking traces the provenance of text produced by large language models by embedding statistically detectable signals during decoding. Existing s
In a recent Twitter exchange, Luca Ambrogioni stated that large‑language models (LLMs) likely possess fundamental limitations that may be obscured by progress in reasoning and agentic pipelines, thoug
Auto mode is now the default in Claude Code for Pro, Max, and Team plans Anthropic are really confident in Claude Code's auto mode, to the point that they are making it the default setting for new ses
arXiv:2608.05165v1 Announce Type: cross Abstract: Speech Emotion Recognition (SER) in low-resource languages remains a challenging problem due to limited labeled data. In this work, we study the use o
arXiv:2608.06023v1 Announce Type: new Abstract: To address the limitations of video-based emotion recognition under ambiguous or socially masked behavioral cues, as well as the poor deployability of p
arXiv:2608.05631v1 Announce Type: new Abstract: Multimodal large language models excel at passive perception but struggle with complex visual cognitive tasks requiring multi-step temporal reasoning. T
arXiv:2608.05993v1 Announce Type: new Abstract: Much clinical value is conveyed not through structured records but through communication: exchanges in which patients describe symptoms, clinicians reas
arXiv:2608.05910v1 Announce Type: new Abstract: Student mobility programs such as Erasmus+ enable students to take courses at other universities, broadening their academic and cultural horizons. Howev
arXiv:2608.05823v1 Announce Type: new Abstract: The reliability of Large Language Models (LLMs) is often compromised by factual inconsistencies, including hallucinations---cases where generated conten
arXiv:2608.06004v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) are currently the best approach to tabular prediction problems. They are constructed as transformers that approximate t
arXiv:2608.06075v1 Announce Type: cross Abstract: Commercial vision-language models are reshaping computer vision, with visual priors broad enough to rival task-specific systems. This raises a natural
arXiv:2608.05695v1 Announce Type: new Abstract: As large language model (LLM) agents increasingly invoke external tools and interact with real-world systems, unsafe actions may cause irreversible cons
arXiv:2608.05605v1 Announce Type: cross Abstract: Research and Education Networks (RENs) serve as critical infrastructure for scientific discovery, yet they face a unique security paradox: their norma
arXiv:2608.05602v1 Announce Type: new Abstract: Generative AI systems are increasingly deployed in high-stakes professional contexts, where their outputs shape what users believe, how they reason, and
arXiv:2608.05313v1 Announce Type: cross Abstract: Service robots operate in household environments shared with humans, pets, and everyday objects, where they are highly susceptible to failures such as
arXiv:2608.06332v1 Announce Type: new Abstract: Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning a
arXiv:2608.05715v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as planners in robotic systems, where they translate natural-language commands into executable
https://x.com/sama/status/2085862292311396515 astra is a powerful model and we are working to make it generally available. we do not think it is a good strategy to keep powerful models to a chosen few
arXiv:2603.26154v2 Announce Type: replace Abstract: Image-to-video (I2V) generation models can be misused to animate a single image into a convincing fake video, motivating perturbation-based image pr
arXiv:2608.05718v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) photogrammetry requires camera networks that provide sufficient surface coverage, image overlap, parallax, and resolution,
arXiv:2608.05493v1 Announce Type: cross Abstract: Language models (LMs) are increasingly used to interact with external services via programs written in domain-specific languages (DSLs). Unfortunately
arXiv:2608.05819v1 Announce Type: new Abstract: Classical simulation remains essential for developing and validating quantum algorithms, but its cost grows rapidly with circuit size. Tensor-network co
arXiv:2608.06135v1 Announce Type: new Abstract: Large Language Models (LLMs) such as ChatGPT and Claude are widely used for information retrieval and problem-solving. Recent work has focused on improv
arXiv:2608.05817v1 Announce Type: new Abstract: Metaphor enables the understanding of abstract concepts through cross-domain mappings while conveying affective attitudes. In multimodal scenarios, visu
arXiv:2608.05243v1 Announce Type: cross Abstract: Factorized generative models commonly regularize a latent style variable z_s by matching its marginal distribution to a fixed Gaussian prior and inter
arXiv:2506.14243v4 Announce Type: replace Abstract: LiDAR-based place recognition is critical for long-term autonomous driving without GPS. Existing handcrafted feature methods face dual limitations.
OpenAI gave a last-minute presentation at the Black Hat security on Wednesday about 'the Hugging Face Incident' (previously on this blog). The video was published yesterday. It's short and information
arXiv:2608.05539v1 Announce Type: new Abstract: Recent vision-language models (VLMs) can generate executable CAD programs from images, but existing methods mainly target coarse, general-purpose 3D obj
arXiv:2608.05990v1 Announce Type: new Abstract: Autonomous agents choose actions using scores that may not reflect experimental success. We developed OPERA, an operator-residual framework for optical
arXiv:2608.05876v1 Announce Type: new Abstract: User requests serve as research specifications for deep research agents, shaping what evidence to seek and how to synthesize it. In personalized deep re
arXiv:2608.05797v1 Announce Type: cross Abstract: Task difficulty dictates an agent's likelihood of success, and estimating it without rollouts means forecasting this directly from a task description
arXiv:2608.06240v1 Announce Type: cross Abstract: Unpaired image-to-image translation must decide, per image, what to change and what to preserve without paired supervision. Many diffusion-based unpai