Knowledge catalogue
arXiv:2610.08691v1 Announce Type: new Abstract: Large language model agents are accelerating scientific automation, yet verified executions rarely become persistent program-level improvements, and exi
arXiv:2610.07558v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have become a major paradigm for Vision-and-Language Navigation (VLN). However, in safety-critical facilities, inv
arXiv:2510.17826v2 Announce Type: replace-cross Abstract: Building a working mental model of a protein typically requires weeks of reading, cross-referencing crystal and predicted structures, and insp
arXiv:2610.07006v1 Announce Type: new Abstract: Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio.
arXiv:2609.33678v2 Announce Type: replace Abstract: We introduce SWE-Game, a benchmark of 247 tasks grounded in 41 executable reference Godot games spanning 13 gameplay categories in 2D and 3D. Five t
This will be a potentially unpopular post - but it's the truth and grounded - so let's get to it. Hopefully you are familiar with my previous Tested in Coding series: https://www.reddit.com/r/LocalLLa
arXiv:2610.08733v1 Announce Type: new Abstract: Language models provide a plug-and-play interface between humans and robots, but important challenges remain when speech, dialogue, fast interaction, an
arXiv:2610.08070v1 Announce Type: new Abstract: Recent diffusion-based image generation backbones have grown substantially in scale, making the network inference cost increase rapidly. While diffusion
arXiv:2610.07899v1 Announce Type: cross Abstract: Generative actors are transforming offline reinforcement learning (RL) by enabling expressive policy classes that model complex action distributions.
arXiv:2610.07987v1 Announce Type: cross Abstract: Multimodal large language models have become the dominant paradigm for visual understanding, but incur substantial costs by encoding inputs into dense
arXiv:2610.07405v1 Announce Type: new Abstract: pass@k, the fraction of problems a model solves within k sampled attempts, is the field's default protocol for deciding whether reinforcement-learning (
arXiv:2610.07269v1 Announce Type: new Abstract: Cross-view geo-localization is commonly solved as an image retrieval problem, matching a ground-level image against a database of satellite tiles throug
arXiv:2610.05281v2 Announce Type: replace Abstract: Modern agents increasingly ground their reasoning in observations returned by tools, such as file contents read from a workspace. However, the data
arXiv:2610.06889v1 Announce Type: cross Abstract: We study the application of large language models (LLMs) to the visual exploration of textual corpora. We introduce zero-shot visualization (ZSV), a t
arXiv:2610.06089v1 Announce Type: new Abstract: Diffusion- and flow-based robot policies have recently become widespread in robotic Imitation Learning (IL) due to their high performance and ability to
arXiv:2610.04801v1 Announce Type: cross Abstract: A useful model of AI inference infrastructure must specify the system state, the information available to an observer, and the decisions the model is
arXiv:2610.05303v1 Announce Type: new Abstract: A large language model (LLM) agent solves long-horizon tasks through many reasoning-action turns, with one verification signal at termination. Deployed
arXiv:2610.06167v1 Announce Type: new Abstract: Zero-shot Neural Architecture Search removes the prohibitive cost of traditional NAS, but its search process is typically based on the evolutionary algo
arXiv:2610.06571v1 Announce Type: new Abstract: Brain MRI interpretation is a longitudinal clinical reasoning problem: radiologists compare serial studies, integrate information across MRI sequences,
arXiv:2610.05870v1 Announce Type: new Abstract: Generative models can synthesize high-quality inauthentic multimedia content that is already being misused at scale. We evaluate twenty deepfake detecto
arXiv:2610.04143v1 Announce Type: new Abstract: Most feature-based choice models, classical and deep, score items and apply a single softmax. We introduce consideration circuits (CC), feature-based mo
arXiv:2510.06842v2 Announce Type: replace Abstract: Action Quality Assessment (AQA) quantifies human actions in videos, supporting applications in sports scoring, rehabilitation, and skill evaluation.
arXiv:2610.04938v1 Announce Type: new Abstract: We propose D-DOIT (Discrete Doob-Oriented Inference-time Transformation), a training-free and efficient adaptation method for discrete diffusion models
On October 6 2026, Georgi Gerganov ( @ggerganov ) announced **day‑0 support for EmbeddingGemma 2 in llama.cpp** on Hugging Face. The announcement linked to the GGUF‑formatted model weights hosted unde
arXiv:2610.03739v1 Announce Type: cross Abstract: The SWOT (Surface Water Ocean Topography) mission is currently providing unpreceded high-resolution measurements of Sea Surface Height (SSH), revealin
arXiv:2610.03833v1 Announce Type: cross Abstract: A novel discovery is one which is both useful and surprising: a generative model's output is a useful discovery if it has a low probability of being g
arXiv:2610.04138v1 Announce Type: new Abstract: Account takeover (ATO) fraud is a growing threat to digital banking, requiring effective detection while minimizing friction for legitimate customers. P
arXiv:2610.06369v1 Announce Type: new Abstract: Integrating environmental sensor data with leaf imagery is widely reported to boost crop disease classification accuracy. In this work, we reveal that t
arXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr
arXiv:2604.01554v2 Announce Type: replace-cross Abstract: Binary Function Similarity Detection (BFSD) is a core problem in software security, supporting tasks such as vulnerability analysis, malware c
arXiv:2610.04283v1 Announce Type: new Abstract: Activation steering exploits interpretable directions in the residual stream to enable inference-time manipulation of model behavior. Composing steering
arXiv:2610.04212v1 Announce Type: new Abstract: Graph Neural Operators (GNOs) provide flexible surrogate models for learning solution operators of partial differential equations (PDEs). However, stand
On October 6 2026 Sophia Yang announced an “open‑source AI week.” She highlighted Monday’s event featuring @reflection_ai’s Beam and Tuesday’s unveiling of @MistralAI’s Mistral Large 4, indicating ant
arXiv:2610.06306v1 Announce Type: new Abstract: General purpose language models are increasingly able to control robotic hardware. Understanding the capabilities and safety of these models when embodi
arXiv:2610.06434v1 Announce Type: cross Abstract: Predicting patient-specific survival functions is crucial for clinicians in making informed decisions about patient care and treatment strategies. Amo
arXiv:2610.04297v1 Announce Type: cross Abstract: Latent safety filters certify safety on a learned low-dimensional representation of the state, enabling constraints that resist analytic description.
arXiv:2610.05538v1 Announce Type: new Abstract: We introduce Loop Flow Transformers (LiFT), a family of looped generative models that scales computation by repeatedly applying a shared Diffusion Trans
Like Jev, I believe RL will unlock several more like this, slashing the cost of critical agent operations. flow-1 is competitive in performance, but a huge cost-saver for finding failures in agent tra
Release: llm-openai-decisions 0.1a0 OpenAI released their new Jev-style Decisions API, as previously announced at last week's DevDay. Since I already have an llm-typesafe plugin for talking to Jev, I
My comment on Mistral Large 4 — Hacker News. wren6991: The benchmark is saturated. Frontier models are tested with an armadillo in fishnet tights jaywalking on Mars. OK well I couldn't resist this one
Mistral Blog: Mistral says it trained ML4 “from scratch” using 3,800 Nvidia Grace Blackwell GPUs in its data centers in Europe and much of its training data was multilingual — Le Chonk — Today, we're
arXiv:2610.05878v1 Announce Type: new Abstract: Benchmarks expose vision-language-action (VLA) policies to few canonical instructions, while exhaustive deployment testing is impossible. We introduce O
arXiv:2610.04657v1 Announce Type: new Abstract: Directed graphs naturally model many real-world systems in which interactions are asymmetric, such as citation networks, web graphs, and information-flo
arXiv:2610.04736v1 Announce Type: new Abstract: A pedestrian with a phone could be shown where nearby people will be in the next few seconds, if the forecast stays on the ground while the phone moves,
arXiv:2610.04100v1 Announce Type: new Abstract: Model compression strategies are widely employed to reduce memory footprint and network complexity, particularly for devices with constrained computatio
arXiv:2610.06103v1 Announce Type: new Abstract: Risk-aware planners score paths on uncertain elevation maps using the path cost's mean and standard deviation. Modeling rigid contact, however, requires
arXiv:2610.05718v1 Announce Type: new Abstract: We introduce Reduced-rank Mahalanobis Distance (ReMaD), a novel prototypical distance-based refinement to classification and out-of-distribution (OOD) d
arXiv:2610.05414v1 Announce Type: new Abstract: Although the advancement of vision-language models (VLMs) has endowed robots with enhanced environmental understanding and task reasoning, a comprehensi
arXiv:2610.05371v1 Announce Type: new Abstract: Ensemble guidance combines pretrained diffusion priors with black-box forward models to solve inverse problems without differentiating through the physi
arXiv:2610.04356v1 Announce Type: new Abstract: Comprehensive 3D scene understanding for autonomous driving requires modeling geometry, semantics, and motion. However, camera-based occupancy and scene
arXiv:2610.05141v1 Announce Type: new Abstract: Controlling the camera relative to a moving subject in an existing video is challenging: behaviors such as maintaining a frontal view require the camera
arXiv:2610.06770v1 Announce Type: cross Abstract: Neural solvers for partial differential equations (PDEs) can approach an accurate solution while their parameters grow without bound. In such cases, t
arXiv:2610.04008v1 Announce Type: cross Abstract: Executable Agent Skills combine natural-language instructions and scripts into reusable packages for LLM agents, and revising them requires fixing err
arXiv:2610.05977v1 Announce Type: new Abstract: Serving a large language model (LLM) across a fleet of deployments requires several weight-precision operating points. Multi-precision formats serve the
arXiv:2610.04467v1 Announce Type: new Abstract: Large language models (LLMs) remain highly vulnerable to jailbreak attacks that induce harmful behaviors and circumvent safety alignment. To defend agai
arXiv:2610.05025v1 Announce Type: new Abstract: Dual-system Vision-Language-Action (VLA) models improve real-time robotic control by pairing a slow, reasoning-capable generalist with a fast specialist
arXiv:2610.04426v1 Announce Type: cross Abstract: Machine unlearning seeks to remove the influence of designated training data from a trained model without retraining from scratch. Retrain-free method
arXiv:2610.04303v1 Announce Type: new Abstract: Recursive computation repeatedly compresses or reuses intermediate states, creating a simple tension: information that must remain useful across longer
arXiv:2610.05322v1 Announce Type: new Abstract: Test-time compute can improve mathematical reasoning, but can short-budget runs predict how mathematical reasoning scales with additional compute? We in
arXiv:2610.04845v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human values is important for safe, efficient, and beneficial AI deployment. However, human values are multif