Knowledge catalogue
arXiv:2610.03265v1 Announce Type: cross Abstract: Large-scale pre-training has improved the generalization of neural operators across diverse PDEs. However, existing PDE foundation models still strugg
arXiv:2610.02678v1 Announce Type: new Abstract: On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher, but providing such supervision for e
arXiv:2610.02248v1 Announce Type: new Abstract: Operational land surface forecasting systems built on Mamba-family Structured State Space Models absorb non-stationary confounding events (unrecorded ir
arXiv:2610.03525v1 Announce Type: new Abstract: Table-to-report generation refers to the task of automatically generating article-level analyt- ical reports from relational tables and is an essential
On my two DGX Sparks, Swift 1.5 (UkisAI's reasoning-efficient fine-tune of Qwen3.8-Flash-Next) running on veloGB10 (https://github.com/sf-stav/veloGB10, sf-stav's Rust/CUDA engine built only for GB10)
arXiv:2610.03329v1 Announce Type: cross Abstract: Large language models are increasingly used where small syntactic errors matter, yet character-level reasoning is still evaluated mostly through isola
arXiv:2609.32791v2 Announce Type: replace Abstract: Reinforcement mid-training lets language models learn internal thoughts from unlabeled text, but efficient token-level credit assignment remains cha
arXiv:2610.03027v1 Announce Type: cross Abstract: The key-value (KV) cache becomes a major memory bottleneck in long-context LLM inference, placing substantial pressure on memory capacity and bandwidt
arXiv:2610.02695v1 Announce Type: cross Abstract: Reliable large language models (LLMs) must not only produce accurate answers but also express confidence that faithfully reflects their probability of
arXiv:2610.02554v1 Announce Type: new Abstract: Offline multi-agent reinforcement learning (MARL) faces a persistent trade-off. Expressive generative policies can represent multi-modal coordination in
arXiv:2508.21143v4 Announce Type: replace Abstract: Cognitive science research treats visual perception, the ability to understand and make sense of a visual input, as one of the early developmental s
arXiv:2610.02404v1 Announce Type: cross Abstract: We study long context language models. Instead of training long context natively, or designing a long context harness, we train a model over the simpl
arXiv:2610.02847v1 Announce Type: cross Abstract: Open-team multi-agent reinforcement learning studies cooperative systems in which agents may join, leave, or be replaced during an episode. In such se
arXiv:2610.03092v1 Announce Type: cross Abstract: Scientific discovery often begins when scattered clues call for a new way of describing the world. Such abductive exploration can require constructing
arXiv:2601.15906v2 Announce Type: replace Abstract: Despite rapid progress in multimodal affective foundation models, how affective capabilities emerge within their internal architectures remains poor
arXiv:2610.03025v1 Announce Type: new Abstract: What makes a short story gripping; a news article newsworthy; or a math proof elegant? These constructs resist articulation or verification; their meani
arXiv:2610.02903v1 Announce Type: new Abstract: We study how to consolidate the current VITOK progress into a single multi-teacher distillation recipe that jointly preserves global recognition and den
arXiv:2610.03234v1 Announce Type: cross Abstract: We present WAMpy, a Python framework optimized for synthesizing Prolog programs. Unlike general-purpose Prolog systems, WAMpy targets workloads that r
arXiv:2610.02491v1 Announce Type: new Abstract: Large language models spend the same amount of computation on every token they generate, regardless of how difficult each token is to produce. Methods s
arXiv:2610.03713v1 Announce Type: cross Abstract: Continual learning treats degradation on previously seen data as evidence of failure, a convention inherited from settings with a stationary predictio
arXiv:2610.03598v1 Announce Type: cross Abstract: Reinforcement learning (RL) is increasingly used for financial optimal-control problems when complex dynamics make analytical strategies difficult to
arXiv:2610.02405v1 Announce Type: new Abstract: Using a frontier model like Claude Opus as a meta-agent to generate terminal tasks and verifiers for RL training is increasingly common. Yet a runnable
arXiv:2610.02508v1 Announce Type: new Abstract: World action models (WAMs) have emerged as a promising paradigm for robotic control by jointly predicting future visual dynamics and actions from an ini
arXiv:2610.03087v1 Announce Type: cross Abstract: Deterministic data loading is important for foundation model development: model researchers need confidence that differences they observe across costl
Banger paper from Google. It's standard practice to sample several agent rollouts and trust the answers they agree on. This Google paper shows that agreement can hide shared errors, while disagreement
Whenever I feed codebases into local models (Qwen, DeepSeek R1) or API models, the biggest annoyance is prompt pollution: - Lockfiles (`Cargo.lock`, `package-lock.json`) burning 30,000+ tokens for zer
Grok 4.7 is #1 on the AA Cyber Index Grok 4.7 xHigh ranked #1 on Artificial Analysis’ Cyber Index Grok 4.7 is now very powerful with serious cybersecurity capabilities It outperformed Claude Opus 5.5,
A while ago I asked here how to turn ~5 million court decisions into structured graphs without running an expensive LLM on every document thanks for the advice . I went with the 'small extractor + cla
I've been looking at the <32B model space and keep coming back to an interesting question. A few years ago, projects like Hummingbird+ suggested that cheap custom accelerators (FPGA-based) might becom
I wanted to know if theres anything that can improve creative writing for our Local Models? I specificly am asking for qwen models as they are way better when it comes to researching and writing html
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Not a bot. Not a Strata shill. Just sharing my experience. So, I have an R9700 in my machine, plus an RTX 5060 Ti, and 64GB DDR5 system RAM. Overall, not a bad setup. Anyway, I mainly run a daily driv
The AI research community released a set of notable papers between September 28 and October 4, highlighted in a weekly roundup. Key contributions include JAZ, CASD, Agensh, Jev‑Mem, AutoGym, Taste‑Ben
Hey everyone, I’ve been working on a game called Anyworld. It’s a browser-based multiplayer (single player also supported) text adventure inspired by the early days of AI Dungeon, especially its brows
So this is maybe a niche problem, but at my job I work on a huge Python codebase and every time I change some shared function I'm basically playing roulette. grep tells who mentions it in the code bas
LWiAI Podcast #258 (recorded 26‑Sep‑2026) reviews major AI updates from the previous week. Key developments include Anthropic’s Opus 5.5 release—offering lower pricing, faster performance and robust b
.@OpenRouter co-founder Alex Atallah, in his first podcast since Stripe acquired the company, joins @Replit co-founder Amjad Masad and a16z's Erik Torenberg on why the future of AI is independence and
We built an engine, Kyojin, on top of ExLlamaV3 for Strix Halo (gfx1151, ROCm), and packed two 300B-class MoE models so each fits one 128 GB machine. First release, all measured on Ryzen AI Max+ 395.
https://unigen-x.github.io/unifolm-wla.github.io/ Unitree Robotics released UnifoLM-WLA-1.0, their new general-purpose humanoid foundation model. Key points: • 6B parameters • Trained on ~2,500 hours
AI researchers Zainhas and Parthsareen from Ollama delivered a breakout presentation on October 2, 2026, focusing on evaluating open-source models under real‑world production traffic rather than just
arXiv:2610.00952v1 Announce Type: cross Abstract: Recaptioned image-text corpora are now standard for text-to-image (T2I) training, with vision--language model (VLM) captioners replacing sparse alt-te
arXiv:2610.01938v1 Announce Type: cross Abstract: Exam-style accuracy does not establish whether large language models (LLMs) reason well over clinical records. We define clinical reasoning as integra
arXiv:2610.01698v1 Announce Type: new Abstract: Active vision manipulation requires a policy to control both its camera and its end-effectors, yet camera motion determines which evidence remains visib
arXiv:2610.01395v1 Announce Type: new Abstract: Muon improves large-scale training by applying a spectral-norm steepest-descent update to matrix parameters, but practical models also contain parameter
Every information technology leader I talk to has an artificial intelligence story about customer experience. Almost none has an outcome story. That gap is now measurable. Talkdesk Inc., in partnershi
arXiv:2610.01389v1 Announce Type: new Abstract: Modern retrieval systems must both be automated and interactive, allowing users to search and refine results in real time. We present AiSearch, a flexib
arXiv:2610.00592v1 Announce Type: cross Abstract: In partially observable reinforcement learning (RL), a later observation can make stored information obsolete or change what it implies for the next d
arXiv:2610.01477v1 Announce Type: cross Abstract: Tracking seasonal change in crops and forests requires observing the same plants repeatedly. Ground robots can do this at close range, and a manipulat
arXiv:2610.01687v1 Announce Type: cross Abstract: Test-time scaling often seeks better answers by sampling multiple responses from a frozen model, yet conventional temperature sampling generates every
arXiv:2507.17389v2 Announce Type: replace-cross Abstract: Recent advances in code large language models (CodeLLMs) have made them indispensable tools in modern software engineering. However, these mod
arXiv:2610.00854v1 Announce Type: new Abstract: Frontier vision-language models (VLMs) combine scene estimation, interaction grounding, and executable actions. Understanding how these abilities suppor
arXiv:2610.01896v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) improves the efficiency of large language model post-training but introduces stale rollouts generated by earl
arXiv:2610.01595v1 Announce Type: cross Abstract: Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet tempo
arXiv:2610.00619v1 Announce Type: cross Abstract: In this paper, we extend earlier findings of supra-competitive outcomes in optimal-execution games by identifying a learned punitive mechanism that de
arXiv:2602.02269v2 Announce Type: replace-cross Abstract: We present multipanda_ros2, a novel open-source ROS2 architecture for multi-robot control of Franka Robotics robots. Leveraging ros2 control,
Somebody just released a fully open-source, open-weights decision model that beats Jev! Just kidding, it's me and I this is my first time releasing a public model, recipe and dataset so I am looking f
arXiv:2610.01530v1 Announce Type: new Abstract: In predictive maintenance, early and late RUL prediction errors carry asymmetric consequences, yet hyperparameter optimization typically targets a singl