Knowledge catalogue
arXiv:2602.03811v3 Announce Type: replace Abstract: A key challenge in autoregressive image generation is to efficiently sample independent locations in parallel, while still modeling mutual dependenc
arXiv:2607.29156v1 Announce Type: new Abstract: AI-generated image forgeries are becoming increasingly realistic and difficult to characterize with fixed manipulation patterns. As generative models co
arXiv:2512.08022v2 Announce Type: replace-cross Abstract: We propose a novel diffusion-based posterior sampling method within a plug-and-play framework. Our approach constructs a probability transport
arXiv:2607.29378v1 Announce Type: new Abstract: Large language models (LLMs) generate text by auto-regressively sampling the next token. This inherently leads to a many-to-many mapping between prompts
arXiv:2607.29555v1 Announce Type: new Abstract: Lacoste-Julien and Jaggi conjectured in 2015 that the pyramidal width of a polytope cannot increase when a vertex is added, provided that every old poin
arXiv:2607.29606v1 Announce Type: cross Abstract: A fundamental challenge of vector search is achieving consistently high recall while minimizing computational costs. Fixed search parameters cause sig
arXiv:2607.29445v1 Announce Type: cross Abstract: Infrared vision-language models (IR-VLMs) extend thermal perception to open-vocabulary classification, image captioning, and visual question answering
Sorry if this is asked a lot, but I was wondering if there is any clear winner on the Quantization versus Model Size debate? I can run Qwen3.6 27b at Q8, Laguna at Q6, and the new Deepseek Flash at Q3
Set up a nightly cron job that executes the prompt: fetch upstream changes to the <software> and rebase all local changes on top of upstream. Check that the software works as intended and replace the
Simon Willison noted that Qwen 3.8 Max and MiniMax‑H3 were released within hours of each other. The MiniMax team announced that MiniMax‑H3 is now publicly available on Hugging Face (https://huggingfac
Qwen3.8-Max (2.4T) is another massive contribution to the open weight community. On benchmarks, it performs closely to Kimi K3 and DeepSeek V4 flash across all categories and is better at coding and s
arXiv:2607.28974v1 Announce Type: cross Abstract: The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To p
arXiv:2602.07339v2 Announce Type: replace Abstract: Diffusion-based trajectory planners can model multi-modal driving behavior, but their iterative denoising process introduces a latency bottleneck fo
arXiv:2607.28879v1 Announce Type: cross Abstract: Similarity search over sparse set-valued data is often dominated by frequent background attributes because classical measures such as Jaccard, cosine,
arXiv:2607.29622v1 Announce Type: cross Abstract: Visual imitation learning enables robots to acquire visuomotor skills directly from images, yet RGB observations lack explicit geometric cues, making
For too long, enterprises with legacy mainframe estates have been faced with a high-stakes dilemma: continue maintaining their mainframes, essentially kicking the modernization can down the road (they
arXiv:2607.28677v1 Announce Type: new Abstract: LLM now pass medical licensing examinations and, in curated cases, can rival physicians at diagnostic reasoning. These developments have accelerated the
arXiv:2607.28995v1 Announce Type: new Abstract: Accurate plant leaf modeling is fundamental to downstream tasks such as plant growth monitoring, and phenotyping for yield estimation. Autonomous roboti
arXiv:2607.29241v1 Announce Type: cross Abstract: Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy change
arXiv:2607.28688v1 Announce Type: cross Abstract: We analyze Reflected UAS routing for heterogeneous multi-server queues at fixed parameters under subcritical load. The deterministic surrogate is a re
arXiv:2607.28908v1 Announce Type: new Abstract: Reflection, the ability to revisit and revise prior reasoning, is central to how humans improve their answers. Large language models (LLMs) are increasi
Hey there! So today we're releasing SupraBrain-50M, a hybrid language model that combines Gated DeltaNet linear recurrence with Sliding-Window Attention and Surprise-Gated update mechanisms to deliver
arXiv:2607.28751v1 Announce Type: new Abstract: Universal multimodal embedding (UME) maps heterogeneous multimodal inputs into a shared embedding space. Existing UME models either form embeddings thro
arXiv:2607.29039v1 Announce Type: new Abstract: Multimodal medical anomaly detection identifies samples deviating from normal patterns, where scarce abnormal cases make normality modeling from normal
arXiv:2507.22580v2 Announce Type: replace-cross Abstract: Automated Program Repair (APR) seeks to automatically correct software bugs without requiring human intervention. However, existing tools tend
An exclusive report by Reuters today has surfaced evidence that suggests Chinese artificial intelligence firms have been leveraging the outputs of American frontier models developed by OpenAI Group PB
arXiv:2607.28776v1 Announce Type: new Abstract: Generative machine learning is increasingly used for inorganic crystal structure generation. Most models and the corresponding evaluation approaches rel
arXiv:2503.15225v3 Announce Type: replace-cross Abstract: The deployment of autonomous virtual avatars (in extended reality) and robots in human group activities---such as rehabilitation therapy, spor
arXiv:2607.29591v1 Announce Type: new Abstract: KV cache compression is essential for efficient long-context inference. Existing eviction methods permanently discard unselected tokens and consequently
arXiv:2606.13316v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a central technique for improving long-horizon reasoning in Large Language Models (LLMs). H
arXiv:2607.29040v1 Announce Type: new Abstract: Deep learning based object detectors require trustworthiness beyond competitive detection performance, but deep neural networks are prone to overconfide
arXiv:2607.28955v1 Announce Type: cross Abstract: AI-generated videos are becoming increasingly realistic and difficult to distinguish from authentic ones, which facilitates malicious misuse and poses
arXiv:2410.06665v4 Announce Type: replace-cross Abstract: This paper explores the characterization of equivariant linear layers for representations of permutations and related groups. Unlike tradition
arXiv:2511.11902v2 Announce Type: replace-cross Abstract: Bidirectional Associative Memory (BAM) trained with Bidirectional Backpropagation (B-BP) often suffers from poor robustness and high sensitivi
arXiv:2607.29412v1 Announce Type: new Abstract: Despite remarkable progress in vision-language generation, Vision-Language Models (VLMs) remain prone to hallucinations, producing content that is incon
arXiv:2607.28814v1 Announce Type: cross Abstract: In Motivational Interviewing (MI), a client's sustain talk (arguments for the status quo) calls for the counselor to roll with resistance, a move that
arXiv:2607.29283v1 Announce Type: cross Abstract: Training large language models (LLMs) to write register-transfer level (RTL) requires large corpora of paired specifications and code, and such data i
I serve a free local model on my Mac Mini and route real agent work to it. To check I was not fooling myself, I set up a blind grader that replays frontier tasks locally and scores both. https://previ
arXiv:2607.17977v2 Announce Type: replace Abstract: We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and p
arXiv:2607.29209v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) sco
arXiv:2607.29569v1 Announce Type: new Abstract: This article presents a modular inference framework that integrates Flow Matching generative models with formal Control Barrier Function (CBF) safety gu
arXiv:2607.28969v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes
arXiv:2607.28685v1 Announce Type: new Abstract: Agent-safety benchmarks measure different behaviors, and their scores get quoted interchangeably as an agent's safety. We treat four of them (R-Judge, I
arXiv:2607.29374v1 Announce Type: new Abstract: Geometry-based grasp planners ensure physically valid grasps but ignore functional semantics, often generating grasps that are antipodal and collision-f
Sakana Namazu: An LLM API with Japanese-vibes! 🎏 Built for Japanese enterprises, featuring frontier-level reasoning and built-in agentic tools. 開発者の皆様、大変お待たせしました！Sakana Chatのモデルが遂にAPIとして公開です。ぜひお試しください
arXiv:2607.29033v1 Announce Type: new Abstract: Existing methods for adapting 2D foundation models such as SAM to 3D volumes either process slices independently---ignoring inter-slice context---or req
arXiv:2607.29294v1 Announce Type: new Abstract: We present HBPI-UCRL, a model-based algorithm for hierarchical reinforcement learning (HRL) that learns high-level and low-level policies in parallel. H
arXiv:2607.29367v1 Announce Type: new Abstract: Satellite image editing requires spatially precise object-level control, but supervised editing datasets for overhead imagery are costly to build becaus
arXiv:2209.05838v2 Announce Type: replace Abstract: Visual layouts of graphs representing SAT instances can highlight the community structure of SAT instances. The community structure of SAT instances
arXiv:2607.28630v1 Announce Type: cross Abstract: Generative AI (GenAI) holds significant promise for advancing educational equity among ethnic minority students by broadening access to learning resou
arXiv:2607.29679v1 Announce Type: new Abstract: We study empirical scaling properties for text conditioning in visual generation. Such properties have rarely been measured because diffusion loss does
arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi
arXiv:2607.29124v1 Announce Type: new Abstract: Scientific figures often encode the visual evidence behind scientific findings, yet figure plagiarism remains underexplored as a benchmarked multimodal
arXiv:2607.28692v1 Announce Type: new Abstract: Large language model (LLM) agents have been increasingly adopted in scientific research for organizing and invoking specialized computational tools. How
arXiv:2607.28759v1 Announce Type: cross Abstract: In X-ray CT, metallic objects cause beam hardening, photon starvation, and scattering, leading to projection inconsistency, streaks, dark bands, and s
arXiv:2607.28693v1 Announce Type: cross Abstract: Industrial NILM remains challenging because measurement noise and widespread concurrent machine operation reduce the generalization of models tuned on
arXiv:2607.28644v1 Announce Type: cross Abstract: Creativity in computational systems is often evaluated as an objective property of artifacts, with existing Computational Creativity (CC) frameworks a
arXiv:2607.29347v1 Announce Type: cross Abstract: Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytic
arXiv:2607.29468v1 Announce Type: new Abstract: Self-play agents can generate training problems without questions from target benchmarks, but their curricula lack persistent state: failures affect gra
arXiv:2607.28777v1 Announce Type: new Abstract: Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized