Search: “models”

arXiv:2605.30290v1 Announce Type: cross Abstract: Self-improvement at scale has been a longstanding goal for reasoning models, and there are two natural places to do it: at test time, through verifica

arXiv:2605.30116v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) is a widely used paradigm for accelerating inference in few-step video diffusion models. However, DMD-style vid

arXiv:2603.17945v2 Announce Type: replace Abstract: In multilingual pretraining, the test loss of a pretrained model is heavily influenced by the proportion of each language in the pretraining data, n

arXiv:2602.01869v3 Announce Type: replace Abstract: LLM-driven agents excel at sequential decision-making but often rely on on-the-fly reasoning, re-deriving solutions even in recurring scenarios. Thi

arXiv:2605.29794v1 Announce Type: new Abstract: LLM agents now draw on growing skill libraries to handle complex tasks. However, injecting more skills does not always improve task completion and can e

arXiv:2605.29188v1 Announce Type: new Abstract: Dictionary methods, topic models, and embedding-similarity scorers are widely used in CSS and management research to measure constructs such as 'entrepr

arXiv:2605.29863v1 Announce Type: new Abstract: Predicting the next mobile application a user will launch is essential for intelligent device resource management and proactive assistance. Existing mod

arXiv:2603.13249v2 Announce Type: replace-cross Abstract: Activation steering offers a computationally efficient mechanism for controlling Large Language Models (LLMs) without fine-tuning. While effec

OpenAI launches Rosalind Biodefense, expanding trusted access to GPT-Rosalind for vetted developers and U.S. government partners advancing biodefense, public health, and pandemic preparedness through

arXiv:2605.29954v1 Announce Type: new Abstract: Sparse vision transformers have gained popularity as efficient encoders for medical volumetric segmentation, with Swin emerging as a prominent choice. S

arXiv:2512.10388v2 Announce Type: replace-cross Abstract: Conventional Sequential Recommender Systems (SRS) typically assign unique hash IDs (HID) to construct item embeddings, which mainly capture co

arXiv:2605.28843v1 Announce Type: cross Abstract: AI is transforming life sciences research at unprecedented speed, accelerating discovery across protein structure prediction, genome modeling, and dru

The blast bent those steel beams on the tower inwards: First look at LC-36 from the air this morning after the explosion of New Glenn last night during a failed hotfire test. Visible is the wreckage f

arXiv:2605.28983v1 Announce Type: cross Abstract: In this paper, training a neural network is identified, exactly, as a search through Hamilton--Jacobi initial-value problems: each gradient step selec

The improvements run wide. Across all major European languages, Command A+ consistently pulls ahead of competitors on WMT24++ (xCOMET-XL): 🇫🇷 +2.4 pts in French 🇪🇸 +1.9 pts in Spanish 🇩🇪 +0.9 pts in G

arXiv:2605.29301v1 Announce Type: new Abstract: The Open Motion Planning Library (OMPL), first released in 2008, has become a cornerstone of the motion planning community, providing implementations of

The story gets bigger beyond Europe. Command A+ makes major gains in high-impact non-Latin languages; outperforming Mistral Medium 3.5 in Korean, Japanese, Hebrew, Chinese, and Arabic. For Arabic, tha

The team at @llama_index built an awesome template using LlamaParse and the new Managed Agents in the Gemini API. See how they built an agent that can tackle unstructured documents. 📄↓ 🚀 The team at @

arXiv:2605.29652v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being used to generate health text from structured records such as wearable time series, biomarkers, vital

this was my pypi hardening strategy for @activegraphai: - spin up a new @replit - point at docs page, ask it to build something - ask it to write a feedback report to package builder - feed that feedb

arXiv:2605.29183v1 Announce Type: cross Abstract: As machine learning(ML) systems evolve to continual adaptation, each re-training cycle uses compute, annotation, and energy. We introduce TIMEGATE, a

arXiv:2605.29380v1 Announce Type: cross Abstract: Mainstream strategies for finetuning pretrained multimodal models often degrade out-of-distribution (OOD) robustness, a phenomenon known as catastroph

arXiv:2605.29153v1 Announce Type: cross Abstract: Neural networks trained under different hyperparameter settings can fall into distinct training 'regimes,' with consistent behavior within regimes and

arXiv:2602.08567v2 Announce Type: replace-cross Abstract: Multi-agent large language model (LLM) systems increasingly consist of agents that observe and respond to one another's outputs. While value a

arXiv:2605.29564v1 Announce Type: new Abstract: When using reinforcement learning (RL) for contact-rich robotic manipulation, vision can provide task-relevant information that accelerates learning bey

VIDEO: @BlueOrigin major New Glenn static fire anomaly at Launch Complex-36 📷 @JerryPikePhoto/@NASASpaceflight Media ANOMALY: @BlueOrigin have suffered a CATASTROPHIC EXPLOSION AT LAUNCH COMPLEX-36 📷

arXiv:2605.29483v1 Announce Type: new Abstract: Wearable devices enable continuous monitoring of physiological signals such as ECG and PPG, but existing mHealth systems are largely limited to task-spe

Watch your avatar speak Spanish, English and Japanese https://x.com/DotCSV/status/2059676610400231599?s=20 Sigo jugando con Omni! Efectivamente el modelo desbloquea un montón de casos de uso (e.g. tra

We’re taking steps to accelerate defensive progress in biology: - Launching Rosalind Biodefense to help trusted builders develop new biodefense and pandemic preparedness capabilities. - Expanding trus

arXiv:2605.28918v1 Announce Type: new Abstract: For sparse, structured reinforcement-learning tasks with semantic reward-function interfaces, LLM-generated reward shaping is better framed as debugging

When we say “LiteParse runs everywhere,” we mean it. Our WASM package is lightweight, minimal, and built for browser and edge runtimes, which makes it a perfect fit for @cloudflare Workers. Using WebA

When you are talking to an LLM, you are speaking to a synthesized work of interactive fiction, not a real being. ChatGPT, Claude, and Sydney are not their neural networks. If any LLM claims to be cons

arXiv:2605.30051v1 Announce Type: new Abstract: A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students,

Windows users, this one’s for you. Computer use now works on Windows, so Codex can take action on your Windows computer. And with Windows support for Codex in the ChatGPT mobile app, you can start, re

This resource discusses how healthcare organizations can build learning health systems to succeed under CMS TEAM (Transforming Episode Accountability Models) and advance value-based care (VBC) initiat

This entry documents a Wordle game result where Anthropic solved puzzle #1,804 in 4 attempts, using color-coded feedback (⬛ = incorrect letter, 🟨 = correct letter wrong position, 🟩 = correct letter co

65B private round More than double the size of the largest IPO ever We've raised 65 billion in Series H funding at a $965 billion post-money valuation, led by @AltimeterCap, Dragoneer, @Greenoaks, and

arXiv:2510.07208v2 Announce Type: replace Abstract: Thompson Sampling is one of the most widely used and studied bandit algorithms, known for its simple structure, low regret performance, and solid th

arXiv:2605.28448v1 Announce Type: new Abstract: Optical tweezers (OT) provide piconewton-scale manipulation for delicate biomedical tasks, where visuo-haptic feedback can improve operator awareness by

arXiv:2605.27789v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems are often compared by asking a large language model (LLM) judge which answer is better. For multi-hop RAG,

arXiv:2605.28703v1 Announce Type: cross Abstract: Baldwinian and Lamarckian evolution have existed for a long time in evolutionary algorithms (EAs) without ever dominating the academic literature or p

arXiv:2511.02398v2 Announce Type: replace Abstract: We present a novel decentralized algorithm for coverage control in unknown spatial environments modeled by Gaussian Processes (GPs). To trade-off be

arXiv:2605.28664v1 Announce Type: cross Abstract: Safety detection models require examples of HHH (Helpful, Harmless, Honest)-violating outputs for robust generalization, however such examples are sca

arXiv:2605.28290v1 Announce Type: new Abstract: We study bandit learning in matching markets, where players and arms constitute the two market sides, and the players' utilities are linear in the arm c

arXiv:2604.04295v3 Announce Type: replace Abstract: Automated patent claim validation demands low error tolerance. However, existing approaches face a rigidity-resource dilemma: lightweight encoders c

arXiv:2605.27531v1 Announce Type: cross Abstract: Specification synthesis, the task of automatically inferring formal specifications from program implementations and natural language, is important for