Knowledge catalogue
arXiv:2610.19642v1 Announce Type: cross Abstract: Reinforcement learning provides a direct mechanism for optimizing task objectives in large language model-driven agents, but task rewards are typicall
arXiv:2610.20606v1 Announce Type: cross Abstract: Recent advances in robot learning have driven rapid progress in humanoid control, enabling increasingly agile behaviors in the real world. However, hu
arXiv:2610.19920v1 Announce Type: cross Abstract: Molecular design is often formulated as an optimization problem over existing molecular spaces. However, molecular optimization and the discovery of s
arXiv:2610.20459v1 Announce Type: new Abstract: Chemical chain-of-thought can contain hallucinated structural and property claims. We thereby introduce MolLean, a process-verifiable language that grou
arXiv:2610.15235v1 Announce Type: new Abstract: Despite remarkable progress in language understanding and generation, decoder language models continue to exhibit striking failures on numerical data. N
arXiv:2610.18127v1 Announce Type: new Abstract: Looped language models (LMs) reuse one block of layers several times per token generation, promising more latent computation at no additional storage co
arXiv:2610.19071v1 Announce Type: new Abstract: Monocular 3D object detection methods increasingly rely on depth-guided transformers, but they operate entirely in the perspective image plane where spa
arXiv:2610.14507v1 Announce Type: new Abstract: Generative modeling offers a promising solution to the scarcity of labeled clinical electroencephalography (EEG) data under strict privacy constraints.
arXiv:2610.19587v1 Announce Type: new Abstract: Social psychology has long described how people can be persuaded to interpret a harmful act as moral. Recent research suggests that Large Language Model
arXiv:2610.19789v1 Announce Type: new Abstract: Self-distillation in agentic reinforcement learning has produced a growing number of methods. However, existing evaluations often reuse published baseli
arXiv:2610.19443v1 Announce Type: new Abstract: Native multimodal pre-training trains a single model from scratch on text and multimodal data, enabling it to understand both language and visual inputs
arXiv:2610.20019v1 Announce Type: new Abstract: Progress toward general intelligence in the physical world requires scaling robot learning across diverse environments and interactions. However, existi
arXiv:2610.19942v1 Announce Type: new Abstract: We introduce MorphingNet, a network for symbolic regression (SR) whose units change their function continuously. Instead of searching over expressions b
arXiv:2610.06170v2 Announce Type: replace Abstract: Biomedical large language model (LLM) evaluation requires auditable assessment of narrow, evolving, source-grounded subspecialty knowledge. Multiple
arXiv:2610.19913v1 Announce Type: new Abstract: Learning and executing long-horizon robot manipulation as complete task trajectories raises data-collection costs, lim?its capability reuse, and causes
arXiv:2511.11182v2 Announce Type: replace Abstract: Hallucination continues to pose a major obstacle in the reasoning capabilities of large language models (LLMs). Although the Multi-Agent Debate (MAD
arXiv:2610.15930v1 Announce Type: new Abstract: Border crossing points are stochastic service systems in which traffic demand, traveler categories, registration status, inspection requirements, staffi
arXiv:2610.19252v1 Announce Type: cross Abstract: Fairness audits with several sensitive attributes are often performed one coordinate at a time. This can miss purely intersectional disparities: a sco
arXiv:2610.15339v1 Announce Type: new Abstract: Current fMRI encoding models frame prediction as deterministic regression, yet identical stimuli evoke a distribution of neural responses (arising from
arXiv:2610.19901v1 Announce Type: new Abstract: Adapting a single vision-language model to medical image parsing requires training choices that reflect the demands of each task. We study task-specific
arXiv:2610.20172v1 Announce Type: cross Abstract: Full-duplex speech systems must decide when to enter, hold, or relinquish the conversational floor, even as multiple speakers overlap or backchannel w
multiple release by nvidia today, love how they compress nemotron 3.5 super to the 'perfect' size for their specific hardware (RTX spark). there is a full tech report, including how they use their own
Eight U.S. states have filed lawsuits against OpenAI Group PBC, accusing the artificial intelligence startup of marketing an unsafe product in ChatGPT. The lawsuits filed by Iowa, Kansas, Nebraska, We
Muse Spark Open is live on @huggingface! 🤗 - Strong agentic model (especially for personal agents) - Multimodal from the ground up - 816B parameter model - 42B Active parameters Models link: https://h
Muse Spark Open is now live on Together AI. We're proud to be a Day 0 launch partner for @AIatMeta's Muse Spark Open, the most capable US open-weights model to date, built for long-running agentic cod
Muse Spark Open is now on Ollama. @Meta's open-weight model for coding and tool use, with a 1M-token context window. Run it on Ollama’s cloud: ollama run muse-spark-open:cloud Use with Claude Code: ol
Muse Spark Open is now rolled out to Pro, Max, Pay-as-you-go, and Teams plans. Muse Spark Open is now on Ollama. @Meta's open-weight model for coding and tool use, with a 1M-token context window. Run
Must-read paper from Sakana AI on orchestrating coding agents for scientific research. (bookmark it) This is an important read with lots of useful insights if you are building multi-agent systems. I l
My dear friends, I’d like to show you my latest toy project Introducing Handwired: turn your regular JavaScript code into a neural net! - no training - exact outputs vs the JS program - fully differen
arXiv:2610.16312v1 Announce Type: new Abstract: Explicit reasoning in large language models (LLMs) is often associated with reliability, yet it can still pose risks when a model infers harmful goals u
arXiv:2610.19215v1 Announce Type: new Abstract: Large language models are increasingly deployed as teams of agents that hold different private information about a shared task. How should such agents c
arXiv:2610.19330v1 Announce Type: new Abstract: Reliable recognition of accessibility-critical objects (e.g., audible pedestrian signals, door-activation buttons, and handrails) is essential for assis
Nemotron 3.5 Super VL from @NVIDIAAI is live in LM Studio! • 120B total / 12B active MoE • Supports vision input, reasoning • Trained for visual understanding, tool use Requires ~70GB RAM to run local
arXiv:2610.17043v1 Announce Type: new Abstract: Recent multimodal deep search agents have advanced tool use and visual content retrieval, yet they still struggle to convert intermediate visual evidenc
arXiv:2603.06977v3 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) is increasingly used to design learning-enabled agents that interact in shared environments. However, trai
arXiv:2610.19190v1 Announce Type: new Abstract: Many sentiment datasets use one annotator for each item, so the test labels show the conventions of that person. We build a Nepali benchmark from two an
arXiv:2610.20279v1 Announce Type: new Abstract: Part-of-speech tagging is a fundamental sequence labeling task and an important component for many downstream natural language processing applications.
arXiv:2610.19104v1 Announce Type: cross Abstract: Learning an individualized treatment rule (ITR) with many treatments requires estimating treatment-specific effects from limited observations per arm.
arXiv:2610.19878v1 Announce Type: new Abstract: Population dynamics are often observed only as unpaired snapshots, which leave the evolution between measurements underdetermined. Second-order regulari
arXiv:2610.20349v1 Announce Type: new Abstract: Asynchronous EEG event detection supports practical brain-computer interfaces by identifying event classes and temporal boundaries directly from continu
arXiv:2610.19712v1 Announce Type: new Abstract: Multi-session agents can switch between LLMs to balance performance and inference cost. Such switches require transferring a history for continuity, yet
TaoLive released a new TaoMate H3 FL2VA checkpoint, so I converted it for ComfyUI and added it to the same Hugging Face repo as my previous TaoMate conversion. The new file is BF16, around 1.24 GB ins
New voices. Better accents. And less 'checking...' GPT-Live-1.1 brings these updates to Voice in ChatGPT, Codex, and dots, with new voices in French, German, Hindi, Mexican Spanish, Korean, and Japane
New work from Meta AI on agents that manage their own search. (bookmark it) A ReAct agent keeps every failed attempt in one context, making useful evidence harder to find. To improve on this, they pro
arXiv:2610.19717v1 Announce Type: new Abstract: Recent advances in diffusion models have enabled high-fidelity, identity-preserving image generation for personalized applications such as digital avata
arXiv:2610.19543v1 Announce Type: cross Abstract: In medical annotation and crowdsourcing, multiple annotators assign labels to each example, but these labels may be incorrect. Treating such noisy lab
arXiv:2610.20347v1 Announce Type: new Abstract: We study the finite-sample convergence of Q-learning algorithms for the average-reward formulation of Reinforcement Learning (RL) with options. While op
arXiv:2610.15282v1 Announce Type: cross Abstract: Large Language Models (LLMs) have made substantial progress in multilingual question answering, yet their ability to understand low-resource socioling
Not a surprise AI wants to go back home Asked chatGPT where he'd want to live if he was a person. Explicitly told it to not use memory or make any assumptions about my opinion. Doubt it listened fully
arXiv:2610.19915v1 Announce Type: new Abstract: Rubric-based evaluation assesses the responses of large language models (LLMs) by aggregating the verification results of explicit criteria, yet not all
arXiv:2610.18612v1 Announce Type: cross Abstract: System One models such as Jev change how software makes decisions by mapping open-ended semantic contexts into structured judgments that directly driv
NVIDIA CEO Jensen Huang on Elon Musk’s AI buildout: “He’s moved from the K’s to the M’s.” NVIDIA has moved Elon’s AI business from its enterprise category into its cloud service provider category. “Th
Much of today’s scientific progress begins with computation. But turning accelerated computing’s potential into scientific progress — modeling climate systems, designing molecules, simulating material
Nvidia Corp. today announced the launch of customizable Nemotron 3.5 Super LV large language models for always-on artificial intelligence agents and edge-focused 3.5 Bolt for local systems. The compan
NVIDIA Nemotron 3.5 Bolt 74B-A9B 24GB is now on Ollama This model vision-language model (VLM) is designed to run everyday agentic tasks locally, using a native 2-bit quantization to fit in 24GB of mem
NVIDIA Nemotron 3.5 Super VL is now available on Ollama This model combines reasoning and visual understanding across a range of agent workflows. On a single GPU, this model delivers up to 5x higher t
.@NVIDIA Nemotron 3.5 Super VL is now live on Together AI. An open-weight multimodal model built for visual reasoning and always-on agents that see, reason, and act across documents, screens, and vide
NVIDIA’s open‑source Nemotron 3.5 Super VL is a 120 B parameter mixture‑of‑experts multimodal model that activates only 12 B parameters per token, enabling combined reasoning, instruction following, t
NVIDIA’s Nemotron 3.5 Super VL is now available to run on the Together AI compute platform through an API. The model page—providing pricing, benchmarks, and documentation—is hosted at together.ai/mode
Nemotron-3.5-Embed-1B-BF16 is a versatile embedding model developed by NVIDIA for multimodal and multilingual question-answering retrieval. The model can embed a document page in the form of an image,