Knowledge catalogue
arXiv:2608.20909v1 Announce Type: new Abstract: Offline RL methods commonly jointly train the actor and critic, where the critic is used to guide the actor toward higher-value actions. This coupled le
arXiv:2602.09716v2 Announce Type: replace Abstract: Computing the importance of nodes in networks is a long-standing fundamental problem that has driven extensive study of various centrality measures.
Standard constrained RL assumes consequences are immediate and attributable to the current action. This breaks down whenever violations are delayed and stochastic, which is most real-world settings yo
arXiv:2608.20759v1 Announce Type: new Abstract: Single-image 3D human reconstruction often suffers from over-smoothed textures and geometric inconsistencies. While diffusion models improve generative
arXiv:2510.12734v2 Announce Type: replace Abstract: Variable importance (VI) methods are often used for hypothesis generation, feature selection, and scientific validation. In the standard VI pipeline
AI agents are the ultimate insiders. We grant them permission to read emails, query databases, and trigger API calls. They don’t just retrieve information, they take action. Agents offer incredible po
arXiv:2608.21218v1 Announce Type: new Abstract: Predictive political question answering (QA), such as predicting how a political actor will vote, goes beyond factual lookup. External political resourc
arXiv:2608.20735v1 Announce Type: new Abstract: Manipulating moving objects requires a policy to anticipate contact events, yet vision-language-action (VLA) policies are commonly fine-tuned from the c
arXiv:2608.21021v1 Announce Type: cross Abstract: Real-world fault analysis in 5G and emerging 6G networks demands domain expertise to analyze free-text diagnostics, including root-cause explanations
arXiv:2606.18250v2 Announce Type: replace Abstract: Forecasting the evolution of dynamic environments is crucial for autonomous agents. While generative world models have achieved high photorealism in
arXiv:2608.20761v1 Announce Type: cross Abstract: In non-stationary multivariate time series, different variables and samples often exhibit heterogeneous latent dynamic states, while existing deep for
arXiv:2608.20748v1 Announce Type: new Abstract: The Visual Geometry Grounded Transformer (VGGT) enables unified feed-forward 3D reconstruction from multi-view images. However, deploying such a high-pe
arXiv:2608.20868v1 Announce Type: cross Abstract: Document processing pipelines traditionally cascade optical character recognition (OCR) engines with downstream models for structured information extr
arXiv:2608.20690v1 Announce Type: cross Abstract: Existing human-object interaction (HOI) motion captioning methods typically describe what happens while referring to the subject using generic terms s
arXiv:2608.20910v1 Announce Type: new Abstract: With large pretrained models, existing methods have effectively improved instruction-based video editing. However, most of them rely on an in-place edit
Interesting new approach to enable memory in long-running agents. Weighted Memory Tree organizes execution into tasks, subtasks, and actions, then gives every memory a retention score that moves. Even
Amazon SageMaker HyperPod now offers managed Ray support on Amazon EKS. Create and monitor Ray clusters, connect JupyterLab and Code Editor notebooks to live clusters, get out-of-the-box observability
arXiv:2603.23463v2 Announce Type: replace-cross Abstract: Recent diffusion-based models achieve photorealism in image inpainting but require many sampling steps, limiting practical use. Few-step text-
arXiv:2608.21134v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) on mobile devices is challenging due to their significant memory and compute requirements. We present a framewor
arXiv:2608.20556v1 Announce Type: new Abstract: Vision-language-action (VLA) models can follow natural-language (NL) task instructions, but such instructions may not precisely specify safety-critical
arXiv:2608.21133v1 Announce Type: new Abstract: Medical image-text data can expose protected health information (PHI) through both visible image content as well as accompanying text, creating a barrie
arXiv:2601.06519v2 Announce Type: replace Abstract: Biomedical retrieval-augmented generation (RAG) can ground LLM answers in medical literature, yet long-form outputs often contain isolated unsupport
MobileMoE is a family of on-device Mixture-of-Experts (MoE) language models with sub-billion active parameters, designed to push the quality–efficiency Pareto frontier for on-device LLMs, including th
My AI broadly agrees with Arvind's AI: state-level data center bans have very little impact overall on AI progress. If your concern is AI development, concentration of power, future use, or anything e
The Register: Nvidia says its Groq 3 LPX racks delivered 3,400 tokens per second in an Artificial Analysis benchmark running Gemma 4 31B with a 100,000-token input sequence — Nvidia's $20 billion bet
arXiv:2608.21209v1 Announce Type: new Abstract: The rise of agentic AI enables LLMs to access diverse user data, raising critical privacy concerns. Prior work on contextual privacy studies whether LLM
arXiv:2608.21031v1 Announce Type: new Abstract: We present PhysCaP, a Physics-Informed Code-as-Policy agent for active perception in robotic manipulation. While vision-language-action policies excel a
arXiv:2608.20432v1 Announce Type: cross Abstract: Formal proofs in Lean 4 that pass the kernel's type checker can nonetheless vary widely in quality. We introduce ProofJudge, an agentic LLM-as-judge s
arXiv:2608.20845v1 Announce Type: new Abstract: Nearly every retrieval-augmented question-answering system in production ships with a hidden interpreter: on each query a language model re-derives the
arXiv:2604.01479v3 Announce Type: replace Abstract: Sparse-view 3D modeling represents a fundamental tension between reconstruction fidelity and generative plausibility. While feed-forward reconstruct
arXiv:2608.20869v1 Announce Type: new Abstract: Predicting transition states (TS) in chemical reactions is crucial, as they provide insights into reaction mechanisms. Recent work on TS prediction have
arXiv:2608.20805v1 Announce Type: new Abstract: Long-form video understanding remains challenging for video agents due to the mismatch between query demands and evidence acquisition strategies. Althou
arXiv:2602.00663v3 Announce Type: replace Abstract: Optimizing molecules to achieve desired properties is a central bottleneck across the chemical sciences, particularly in the pharmaceutical industry
arXiv:2608.21203v1 Announce Type: new Abstract: Technology change management in large financial institutions depends on risk assessments that are accurate, consistent, and auditable. In practice, many
arXiv:2608.21044v1 Announce Type: new Abstract: Class-incremental learning is commonly instantiated as a single-model paradigm, where a unified model sequentially adapts to an unbounded stream of sess
arXiv:2608.20802v1 Announce Type: new Abstract: Human motion forecasters are increasingly accurate and fast, but reliable deployment requires uncertainty estimates that are structured, calibrated, and
arXiv:2504.18882v3 Announce Type: replace-cross Abstract: Neuroimaging provides essential tools for characterizing brain activity, structure, and connectivity through modalities that capture complemen
arXiv:2608.20414v1 Announce Type: new Abstract: Vision-language models are increasingly used for multimodal question answering, yet their ability to reconstruct latent spatial structure from a single
arXiv:2608.20597v1 Announce Type: cross Abstract: Agentic AI systems are being procured for military command and control (C2) under public commitments to rigorous testing and human oversight. Whether
arXiv:2608.21276v1 Announce Type: cross Abstract: Coastal environments contain rich, largely unexploited geometric structure capable of providing globally referenced localization cues. In this work, w
arXiv:2608.20494v1 Announce Type: cross Abstract: Multi-agent LLM systems are an emerging networked workload whose rapid deployment raises questions about the traffic patterns they generate. Compared
arXiv:2608.20809v1 Announce Type: cross Abstract: Breast ultrasound diagnosis relies on clinically meaningful semantic concepts, yet most deep learning methods adopt end-to-end image-to-label paradigm
arXiv:2608.21095v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) outputs in external knowledge, but RAG systems usually trust whatever they ret
arXiv:2504.09772v3 Announce Type: replace Abstract: Test-Time Scaling has emerged as a powerful method to extend the reasoning capabilities of Large Language Models. However, single-agent TTS faces si
arXiv:2608.20974v1 Announce Type: cross Abstract: Video Joint Embedding Predictive Architecture (V-JEPA) learns powerful spatiotemporal representations from video through self-supervised latent featur
arXiv:2608.20631v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated the ability to solve multi-step tasks requiring planning, tool use, and external information access,
arXiv:2608.21098v1 Announce Type: new Abstract: Fusing prior knowledge with data-driven learning is attractive where data is scarce, yet no controlled account says when it helps, is redundant, or harm
Given OpenRouter.ai was snapped up by Stripe, who do we think would go after the 'GitHib' of AI models? It is a big chunk of change they are looking ($13B). Apple may be a contender to give them a rea
arXiv:2608.20670v1 Announce Type: new Abstract: Many agentic systems must repeatedly choose between acting and abstaining, making faithful reasoning important for oversight: an explanation is useful o
More data than open-source AI is taking share from OpenAI and Anthropic. Open source has gone from 28% token share to 62% token share @vercel over the last 2 months. Chart from @rauchg Super impressiv
Hey everyone! Last year, Mozilla released Orbit, an AI-powered browser summarizer hosted on a GCP server. After people started digging into the extension, they discovered things like backend endpoints
Hey everyone! Last year, Mozilla released Orbit, an AI-powered browser summarizer hosted on a GCP server. After people started digging into the extension, they discovered things like backend endpoints
Our devs got their hands on it a few days ago. One wired it into Codex to compare with GPT Luna, our usual workhorse right now for its cost effectiveness. Another tried it out on one of our OCR pipeli
You don't often see one-word titles in AI papers. That aside, strong recommend this paper from Google DeepMind. I think this is an interesting training-free approach to evolve model architectures by l
Great paper if you are tracking progress in recursive self-improvement (RSI). (bookmark it) There is so much hype around RSI, so I think it's worth understanding why current models are not able to do
I've been trying to figure out what the best configuration for my local stack would be and have been primarily determining this through trial and error. I wanted to get some outside opinions and stack
This is one of the most effective ways to improve your agentic workflows. If you are building computer-use agents, this one is worth your time. Task Model Induction takes a raw recording of someone wo
What a fascinating paper on AI agents. A lot of the issues we see with AI agents today revolve around wrong assumptions the LLMs make. This leads to problems like hallucination, cost inefficiencies, u
arXiv:2608.19504v1 Announce Type: new Abstract: We propose a conditioning mechanism for diffusion models based on multi-speed joint diffusion of the target and the condition. The mechanism learns an u
arXiv:2605.05488v2 Announce Type: replace Abstract: We propose an architecture that augments the Flux Neural Operator (Flux NO), which combines the classical finite volume method (FVM) with neural ope