Knowledge catalogue
arXiv:2506.18164v2 Announce Type: replace Abstract: Cross-view masked autoencoding has emerged as a powerful pretext task for learning dense correspondences, which are essential for applications such
arXiv:2608.01725v1 Announce Type: cross Abstract: Modern computing and networking infrastructure emits telemetry continuously, yet operators convert it into decisions with a separate predictor per tas
arXiv:2608.01821v1 Announce Type: new Abstract: Diffusion vision-language models (dVLMs) iteratively denoise masked responses while conditioning each denoising step on visual evidence, making visual c
arXiv:2608.00793v1 Announce Type: new Abstract: Dynamic manipulation requires robots to infer target motion and respond promptly, yet existing World-Action Models (WAMs) typically condition only on th
arXiv:2409.05885v2 Announce Type: replace Abstract: Characterizing nonlinear flame response is critical for predicting thermoacoustic instabilities in propulsion combustors, yet obtaining a comprehens
arXiv:2608.01663v1 Announce Type: new Abstract: Promptable segmentation foundation models (FMs) such as SAM3 and Medical SAM3 promise few-shot, interactively-specified segmentation for medical imaging
arXiv:2608.01547v1 Announce Type: cross Abstract: Drifting objectives compare a target and model distribution through a vector field observed noisily at finitely many locations. We ask what distributi
arXiv:2608.01265v1 Announce Type: cross Abstract: Despite recent progress in Vision-Language-Action (VLA) models for robotic manipulation, the action chunk remains a weakly structured interface. Exist
Today, we are introducing the general availability of Web Search on Amazon Bedrock. It is a server-side built-in tool that grounds model responses in current web knowledge. With Web Search, grounding
arXiv:2510.20449v2 Announce Type: replace Abstract: Instruction tuning is crucial for aligning Large Language Models (LLMs), yet the quality of instruction-following data varies significantly. While h
arXiv:2608.01332v1 Announce Type: cross Abstract: Scenario-tree model predictive control (MPC) represents future information by a rooted tree and optimizes a nonanticipative policy over that tree. Num
arXiv:2608.01535v1 Announce Type: new Abstract: Vision-language models (VLMs) are emerging as a key component of embodied intelligence, with growing applications in auto-labeling and end-to-end autono
arXiv:2608.02070v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) have been widely used in motor rehabilitation, disease diagnosis, and other neural engineering scenarios. However, conv
Mistral AI has released Shieldstral, a 3‑billion‑parameter open‑weight model for content safety that can run locally on device. It interprets plain‑language moderation queries and returns calibrated s
arXiv:2608.02137v1 Announce Type: new Abstract: Vision-language models (VLMs) exhibit strong generalization across multimodal tasks but remain vulnerable to adversarial perturbations. Existing attacks
arXiv:2608.01573v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models achieve promising performance in robotic manipulation, typically measured by success rates aggregated over pr
arXiv:2608.01845v1 Announce Type: cross Abstract: Diffusion world models generate high-quality futures, but re- peated transformer evaluations make inference prohibitively slow. Existing caches reuse
arXiv:2606.20324v2 Announce Type: replace-cross Abstract: Virtual training environments are software-intensive systems in which reinforcement learning (RL) agents learn, adapt, and demonstrate meaning
arXiv:2607.28707v1 Announce Type: new Abstract: Entropy-based pruning has been proposed as an effective method for compressing Chain-of-Thought (CoT) reasoning with negligible accuracy loss. We test t
arXiv:2607.28971v1 Announce Type: cross Abstract: Contrastive learning is widely used for user modeling in large-scale recommender systems, where standard in-batch negatives implicitly assume universa
arXiv:2602.02685v3 Announce Type: replace Abstract: Decentralized Diffusion Models (DDMs) route denoising through experts trained independently on disjoint data clusters, which can strongly disagree i
arXiv:2607.28762v1 Announce Type: new Abstract: This work embeds feature interaction modules derived from factorization machines (FMs) into physics-informed neural networks (PINNs) and neural operator
arXiv:2607.29596v1 Announce Type: cross Abstract: Vision-language-action models (VLAs), which leverage the cognition of multimodal information to infer physical-world actions, provide a generalized so
Finally a good paper testing whether agent memory needs an LLM at all. Production memory stacks spend extra model calls on summarizing interactions, writing records, and reranking retrievals. Every on
GPT-Live can listen while it speaks. To make that feel natural at ChatGPT scale, we rebuilt the voice stack from client to model. This new architecture keeps audio flowing continuously, so deeper reas
Hugging Face CEO says China is winning the AI race and dominating on open models https://www.cnbc.com/2026/08/03/hugging-face-china-ai-race-open-models.html?taid=6a70b9a7142a0e000189af30&utm_campaign=
arXiv:2607.28696v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) can retain high observed marginal coverage after clinical shift while substantially under-covering an individual
Most companies still rent AI by the token, build on someone else’s roadmap, and hope the next model release does not disrupt their systems. At ODSC AI West 2026, @Prof_OZ, Head of AI Developer Educati
Hermes Agent is now dramatically more efficient, especially for smaller/weaker/local models! With the help of @nvidia's Nemo Relay and several other strategies Hermes was able to identify a ton of opt
It feels like Ollama’s brand identity has shifted. It used to be centered on self‑hosted models, but now most of the new releases seem to be API‑based services with far more emphasis on cloud integrat
Kimi K3 has set a new bar for OSS model intelligence! 2.8T params, 1M context, OpenAI-compatible API. Complete guide to running Kimi K3 on Together AI 👇 👏👏 @Kimi_Moonshot 👏👏 https://www.together.ai/bl
arXiv:2607.15715v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used for complex information-extraction tasks, yet it remains unclear whether agentic components
arXiv:2607.28410v1 Announce Type: cross Abstract: Parent-order execution is a core problem in algorithmic trading, where the goal is to split a large order into smaller orders while reducing execution
arXiv:2607.27756v1 Announce Type: cross Abstract: Spoken dialog systems are typically designed for clean, dyadic interactions in which a single user and an assistant take turns speaking. Real-world so
arXiv:2607.28460v1 Announce Type: new Abstract: A major issue in Security Operations Centers (SOCs) is alert fatigue, as the number of detections reported is more than staff can triage in a given day.
arXiv:2607.27511v1 Announce Type: new Abstract: Imitation learning has shown increasing promise for autonomous robotic surgery, yet safe deployment remains challenging due to the safety-critical natur
Fine-tune your own embedding model for the price of a coffee. A great reranker can't surface a doc that was never retrieved. A RAG pipeline cannot cite a case it failed to retrieve. See how contrastiv
arXiv:2607.28397v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) over knowledge graphs requires retrievers that can effectively capture both graph structure and semantic informat
Inkling-Small is now live on Together AI. @thinkymachines’ new open-weight multimodal model delivers similar performance to Inkling at one-quarter the size, built for coding, agents, and general multi
arXiv:2607.27482v1 Announce Type: cross Abstract: A temporally drifting data stream may pass through discrete regimes rather than changing continuously. We ask whether such regimes are recoverable fro
arXiv:2503.15846v2 Announce Type: replace Abstract: Dynamic Scene Graph Generation (DSGG) aims to capture objects and their evolving relations in videos. Despite recent progress, the practicality and
arXiv:2607.26726v1 Announce Type: new Abstract: Emotion Recognition in Conversation (ERC) aims to predict utterance-level emotions in dialogues and has largely advanced through context-centric modelin
Excited to work with the @IntelBusiness team on enabling open models with Intel Core Ultra Series 3. Built to bring open-source LLMs to private machines, @Ollama uses Intel Core Ultra Series 3 to run
arXiv:2607.26442v1 Announce Type: cross Abstract: At parking speeds, the kinematic bicycle is the prevailing model for car-like vehicles. Yet, despite its wide use, stabilizing feedback laws for this
arXiv:2607.26602v1 Announce Type: cross Abstract: The rapid development of the Internet of Everything (IoE) is accelerating the adoption of intelligent applications. However, the massive number of con
arXiv:2505.01043v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t
arXiv:2607.26991v1 Announce Type: new Abstract: Despite the impressive visuomotor capabilities enabled by Vision-Language-Action (VLA) models, their performance often degrades on challenging and out-o
arXiv:2603.27519v2 Announce Type: replace Abstract: Image-based plant phenotyping depends on dense structural understanding of crops, yet pixel-level annotation remains expensive across species, organ
arXiv:2607.26984v1 Announce Type: cross Abstract: Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modelin
arXiv:2607.26207v1 Announce Type: new Abstract: Brain tumors such as glioma, meningioma, and pituitary adenoma alter the mechanical behavior of soft brain tissue, yet common diagnostic methods rely on
arXiv:2602.09611v2 Announce Type: replace-cross Abstract: Watermarking has emerged as a pivotal solution for content traceability and intellectual property protection in large vision language models (
The Together AI platform’s dedicated inference architecture consists of three immutable entities: **configs** (engine, GPU type/count, parallelism and optimization profile), **deployments** (a specifi
arXiv:2607.25802v1 Announce Type: new Abstract: Most video editing systems still lack explicit layered video representations, limiting their ability to perform realistic compositing, object reuse, and
arXiv:2607.00078v2 Announce Type: cross Abstract: We propose a Transformer-based Reinforcement Learning architecture, 'LB-Explorer', to search for heterotic line bundle standard models arising from co
arXiv:2607.24797v1 Announce Type: cross Abstract: In the literate human brain, reading and writing are two doubly-dissociable systems: a ventral decoding route (impaired in pure alexia) and a fronto-p
arXiv:2607.25818v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs), such as Qwen2.5-VL and InternVL3, generate large numbers of vision tokens for high-resolution inputs, l
arXiv:2607.25333v1 Announce Type: cross Abstract: Specula is a push-button agentic system that generates high-quality formal specifications for large, complex system code and uses the specifications f
arXiv:2607.23486v1 Announce Type: new Abstract: Dissolved gas analysis (DGA) is crucial for diagnosing early power transformer failures. Traditional DGA interpretation methods like Duval Triangle, IEC
arXiv:2607.23067v1 Announce Type: cross Abstract: Contrastive decoding methods such as DoLa improve the factuality of Large Language Models (LLMs) by contrasting the output distributions of mature and
arXiv:2607.22539v1 Announce Type: cross Abstract: The Radiotherapy Scheduling Problem (RTSP) involves determining an optimal schedule for patients undergoing radiation treatments, a task that has a ma