Knowledge catalogue
arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate m
arXiv:2608.18647v1 Announce Type: new Abstract: Autonomous endovascular navigation could support the delivery of mechanical thrombectomy to underserved areas, but controllers must navigate long, multi
arXiv:2608.18643v1 Announce Type: new Abstract: Researchers often choose a proxy dataset from many releases, transformations, or seeds. Search can make an invalid release appear adequate, while one ad
I had mistakenly been using a base for H3 prompting from some random tip / example by someone. It worked ok, I thought. But I was getting a bit frustrated because almost every time I was making a long
Qonto's help page describes live Operator and Analyst agents, user approval for actions and EU data hosting, but no measured customer outcome.
arXiv:2608.18659v1 Announce Type: cross Abstract: Tsetlin Machines (TMs) learn interpretable Boolean clauses using finite-state automata. We introduce the Quantum-Logic Tsetlin Machine (QL-TM), which
arXiv:2608.18901v1 Announce Type: cross Abstract: Tensor Networks are a relatively new machine learning approach. The architectures proposed initially are inspired by approaches from quantum many-body
arXiv:2608.18285v1 Announce Type: cross Abstract: 3D scene representation techniques such as neural radiance fields (NeRFs) and Gaussian splatting have made substantial progress in novel view synthesi
I'm testing it since release, now with UD 3.0 in my AMD R9700 with ROCm, I always read everywhere that F16 and q8_0 for KV cache are essentially the same... well, I tested it and I can see differences
Qwen 3.8 27B now runs locally inside RunAnywhere! Your app can use the same local AI setup across different hardware. On Mac it runs Swift + mlx. On Windows, Electron + llama.cpp. Different architectu
Off a single prompt, given my credentials and the name of my university, qwen3.8-27b was able to successfully pull my class schedule from the kinda shitty and convoluted web of university websites. It
https://reddit.com/link/1vtkgdj/video/595yn0ckdjkh1/player I wanted to try out Qwen3.8 27B 's SVG capabilities but with something different than the pelican on a bicycle. Promt was literally just : cr
I benchmarked Qwen3.8-27B on MathArena/aime_2026 dataset, comparing BF16 and FP8 weights at medium and xhigh reasoning effort. Interesting findings are: quantized FP8 xhigh is better than BF 16 medium
Like many of you I've spent the last few days throwing Qwen3.8-27B against all of my usual use-cases and personal tasks/harnesses and workflows. It's great, phenomenal sometimes, but that's not what t
I chose to do this thing, not because it was hard, but because it was silly. Posts kept discussing how 3.8 and 3.6 were functionally the same, but based on training (3.8 does have seven new tokens!)..
Ram Iyer / TechCrunch: Ramp launches Router, an AI model routing service it has been using internally over the past three years, in the US; Router is free to use for the rest of 2026 — Corporate expen
arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical s
arXiv:2608.18768v1 Announce Type: new Abstract: Large language models are widely used to simulate survey respondents, yet their answers are homogeneous and unfaithful to real inter-group differences.
arXiv:2608.18552v1 Announce Type: new Abstract: This paper presents a real-time control-constrained Differential Dynamic Programming (DDP) framework for underactuated legged robots. To address the lim
arXiv:2405.15336v2 Announce Type: replace Abstract: Continuum robots are slender, flexible manipulators that navigate confined, curved workspaces and are gaining traction in aerospace, inspection, aut
arXiv:2608.18260v1 Announce Type: new Abstract: Large Language Models (LLMs) are being increasingly used in everyday applications. A major challenge in the context of LLMs or Artificial Intelligence (
arXiv:2608.18952v1 Announce Type: cross Abstract: Large language models can improve recommendation quality by reasoning explicitly over user history and candidate items - for example, extracting a use
arXiv:2608.18742v1 Announce Type: cross Abstract: In some fields currently dominated by empirical approaches, such as state of health (SoH) prediction for lithium-ion batteries, phenomenological model
arXiv:2608.18669v1 Announce Type: new Abstract: Humans solve complex problems by constructing plans and mentally simulating their outcomes with an internal model of the world. Machine learning has pro
arXiv:2511.12850v2 Announce Type: replace Abstract: Topic models are often judged by the consistency of their outputs across repeated runs, implicitly assuming that repeatable topic output is a succes
Replit announced its Free Mode on August 20 2026, powered by OpenAI’s GPT‑5.6 Luna, to provide broader, no‑cost access to AI capabilities. The launch highlighted an effort to make intelligent tools mo
Anthropic PBC is privately hoping its upcoming initial public offering will match or even surpass the size of SpaceX Corp.’s record-breaking IPO as it doubles down on its bid to go public ahead of riv
arXiv:2608.18317v1 Announce Type: new Abstract: Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction m
arXiv:2608.18271v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own responses using token-level supervision from the same model conditioned on privileged ref
arXiv:2608.18227v1 Announce Type: new Abstract: Push-T is an iconic benchmark for learning manipulation policies from human demonstrations. The robot must use a single point of contact to push a T-sha
arXiv:2608.19075v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate, generating content that the input image does not support. Preventing such content during decod
arXiv:2608.18593v1 Announce Type: new Abstract: Single-image rephotography aims to synthesize new shots of a scene from a single reference image with specified viewpoints, focal lengths, and photograp
arXiv:2608.18948v1 Announce Type: new Abstract: Collecting robot hand-object interaction data is costly and embodiment-specific, yet abundant human-object videos remain unusable for robot training. We
arXiv:2608.19073v1 Announce Type: new Abstract: An agent still learning its environment should be cautious while ignorant and bold once confident. The entropic value-at-risk captures this through a ro
arXiv:2607.15048v2 Announce Type: replace Abstract: Road surface mapping plays a crucial role in autonomous driving, supporting high-definition map generation, lane-level perception, and automatic roa
arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficie
arXiv:2607.16230v2 Announce Type: replace-cross Abstract: Accurate pre-order shipping cost estimation is important in e-commerce because it affects price presentation, margin planning, and conversion.
arXiv:2608.18682v1 Announce Type: new Abstract: Training multi-turn agentic workflows with reinforcement learning (RL) enables large language models to perform complex reasoning, use external tools, a
arXiv:2608.18864v1 Announce Type: new Abstract: LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typica
arXiv:2608.18190v1 Announce Type: new Abstract: Domain adaptation is widely used to make neural networks trained on simulations applicable to experimental data. Its premise is that the two domains dif
arXiv:2608.18131v1 Announce Type: new Abstract: Current safety alignment training for Large Language Models (LLMs) are heavily English-centric. When such safety filters fail for non-English languages,
arXiv:2608.18640v1 Announce Type: new Abstract: Long-term video object segmentation (VOS) remains challenging due to error accumulation under extended occlusions, re-appearance, and scene changes. Alt
arXiv:2608.18108v1 Announce Type: cross Abstract: Large language models are being incorporated into sensitive and important decision-making processes across nearly all fields. While prior work studies
Veeda AI, a startup led by a team of former Nvidia Corp. researcher and renowned computer scientist Sanja Fidler, has taken its bow on the main stage after raising 90 million in a seed funding round t
arXiv:2608.18677v1 Announce Type: new Abstract: Amid concerns that generative AI may standardize art interpretation, this paper examines whether LLM-based interaction can support plural art-historical
arXiv:2608.18611v1 Announce Type: new Abstract: Electric power networks are increasingly exposed to weather-sensitive failure mechanisms that require asset-level, spatially explicit risk modelling for
Scaling agentic AI across an enterprise requires patterns that preserve flexibility while avoiding vendor lock-in. In this second post of our multi-agent series, we examine how ML teams operate many a
Learn how AWS Professional Services uses a multi-agent framework built on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Purpose-built AI agents handle discovery, infrast
arXiv:2608.18140v1 Announce Type: new Abstract: We define an intertwined scheduling and routing problem where new jobs appear due to the degradation of the existing jobs. Specifically, once a job arri
arXiv:2608.18508v1 Announce Type: cross Abstract: We are witnessing an explosion of agentic systems for computational chemistry simulations: from half a dozen in 2024 to a dozen in 2025, and the curre
arXiv:2608.19134v1 Announce Type: new Abstract: Accurate visual decoding can reveal how the brain represents visual information and recover perceived content from neural signals such as electroencepha
arXiv:2608.18918v1 Announce Type: new Abstract: Dimension reduction for dynamical systems is standard practice, and the standard route is spectral: model the transfer (Koopman) operator by its leading
arXiv:2608.18174v1 Announce Type: cross Abstract: Customer decline early-warning systems feed account-manager action lists, and every flagged account consumes intervention capacity. In a deployed busi
arXiv:2608.18755v1 Announce Type: new Abstract: Synthetic aperture radar (SAR) object detection is an important part of remote sensing interpretation. However, because of variations in frequency band,
Seeing a hype wave around GEN-1.5, and rightfully so. Lots of respect to Pete & Andy for executing so well. The secret is in the naturally repetitive motions in human-collected data. There're 2 main s
arXiv:2608.18272v1 Announce Type: cross Abstract: Classical seismic data reconstruction relies on manually designed structural priors and iterative operators, whose coupled design space is far larger
arXiv:2608.18379v1 Announce Type: cross Abstract: When every candidate is wrong, correct-candidate selection is unavailable, yet the aggregation call can still solve the problem afresh. A correct aggr
arXiv:2608.18091v1 Announce Type: cross Abstract: As LLM-as-a-judge systems become increasingly widespread, self-preference in LLMs -- the tendency to favor one's own outputs -- raises growing concern
arXiv:2608.18104v1 Announce Type: new Abstract: Large language model (LLM)-based agents are increasingly becoming self-evolving systems that persist across interactions, maintain memories, use tools,
arXiv:2603.25681v2 Announce Type: replace Abstract: As large language models (LLMs) continue to advance, improving them solely through human supervision is becoming increasingly costly and limited in