Search: “model-releases”

arXiv:2603.24621v2 Announce Type: replace Abstract: We introduce ARC-AGI-3, an interactive benchmark for studying agentic intelligence through novel, abstract, turn-based environments in which agents

arXiv:2504.10466v2 Announce Type: replace Abstract: Large-scale pre-trained image-to-3D generative models have exhibited remarkable capabilities in diverse shape generations. However, most of them str

arXiv:2601.07160v2 Announce Type: replace Abstract: To meet the ever-increasing demand for computational efficiency, Neural Processing Units (NPUs) have become critical in modern AI infrastructure. Ho

arXiv:2604.16286v1 Announce Type: new Abstract: As AI systems are increasingly used to conduct research autonomously, misaligned systems could introduce subtle flaws that produce misleading results wh

arXiv:2604.16158v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly rely on chain-of-thought (CoT) reasoning to solve complex tasks. Yet ensuring that the reasoning trace both

Attending #AIDev26 by @DeepLearningAI? Join @AI21Labs, @trychroma + @Baseten for a panel on optimizing modern AI systems. Drinks. Nikkei food. No fluff. April 28 | 5PM | Kaiyō SF Register → http://lum

arXiv:2512.24625v2 Announce Type: replace-cross Abstract: Accurate traffic prediction is essential for Intelligent Transportation Systems, including ride-hailing, urban road planning, and vehicle flee

arXiv:2604.15332v1 Announce Type: cross Abstract: Crash diagrams are essential tools in transportation safety analysis, yet their manual preparation remains time-consuming and prone to human variabili

arXiv:2604.16241v1 Announce Type: cross Abstract: Large language models have shown strong performance on broad-domain knowledge and reasoning benchmarks, but it remains unclear how well language model

arXiv:2604.15808v1 Announce Type: cross Abstract: Spatial reasoning and visual grounding are core capabilities for vision-language models (VLMs), yet most medical VLMs produce predictions without tran

arXiv:2604.16259v1 Announce Type: cross Abstract: Frontier models have demonstrated exceptional capabilities following the integration of task-reward-based reinforcement learning (RL) into their train

Beyond generating high-fidelity visuals, we wanted to test the limits of what Nano Banana Pro can do. We worked with design partners Porto Rocha to build out a hypothetical brand called YOYOYO to see

arXiv:2510.24328v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used to answer everyday questions, yet their performance on culturally grounded and dialectal co

Boston Dynamics just gave its robot dog a brain that reasons about the physical world. Google DeepMind's Gemini Robotics model is now running inside Spot, the four-legged robot already deployed at tho

arXiv:2604.15821v1 Announce Type: cross Abstract: Universal Machine Learning Interatomic Potentials (uMLIPs), pre-trained on massively diverse datasets encompassing inorganic materials and organic mol

Calling all builders 🛠️📣 Google AI Pro and Ultra subscribers will now get increased usage limits and access to Nano Banana Pro and Gemini Pro models in @GoogleAIStudio — no API key required. Sign in w

arXiv:2604.16258v1 Announce Type: new Abstract: Competency Questions (CQs) are a cornerstone of requirement elicitation in ontology engineering. CQs represent requirements as a set of natural language

arXiv:2508.10635v3 Announce Type: replace Abstract: Understanding environmental changes from remote sensing imagery is vital for climate resilience, urban planning, and ecosystem monitoring. Yet, curr

Check out our repository below, self host your own version of claude code for investment in just three commands! https://github.com/ginlix-ai/LangAlpha LangChain Community Spotlight: LangAlpha 💼 A cod

arXiv:2604.16205v1 Announce Type: cross Abstract: Computational X-ray absorption near-edge structure (XANES) is widely used to probe local coordination environments, oxidation states, and electronic s

arXiv:2604.15802v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems lose retrieval accuracy when similar documents coexist in the vector database, causing unnecessary informat

Classic study gave 146 economist teams the same dataset & got wildly different answers New paper reruns it with agentic AI. Claude Code & Codex land near the human median, but with far tighter dispers

Claude Design rocks and Claude Design sucks. Let's talk about. Last night, I created an entire game in Claude Design inspired by the Longyou Caves in China (why is there no soot!), and we all gathered

Claude Token Counter, now with model comparisons I upgraded my Claude Token Counter tool to add the ability to run the same count against different models in order to compare them. As far as I can tel

Gary Marcus argues that Claude's internal representations described as 'emotion vectors' are not genuinely emotional in nature, drawing an analogy to how counterfeit money mimics but lacks the essenti

arXiv:2604.15663v1 Announce Type: cross Abstract: Code search, framed as information retrieval (IR), underpins modern software engineering and increasingly powers retrieval-augmented generation (RAG),

arXiv:2604.15001v2 Announce Type: replace Abstract: LLM-based RTL code generation methods increasingly target both functional correctness and PPA quality, yet existing approaches universally decouple

arXiv:2602.01766v2 Announce Type: replace-cross Abstract: The quadratic complexity and indefinitely growing key-value (KV) cache of standard Transformers pose a major barrier to long-context processin

arXiv:2510.07043v2 Announce Type: replace Abstract: Human decision-making often involves constrained optimization. As LLM agents are deployed to assist with real-world tasks like travel planning, shop

arXiv:2603.08899v2 Announce Type: replace Abstract: Speculative decoding has emerged as a powerful approach to accelerate large language model (LLM) inference by employing lightweight draft models to

arXiv:2604.15547v1 Announce Type: cross Abstract: The fundamental challenge of using Large Language Models (LLMs) for reliable, enterprise-grade analytics, such as sentiment prediction, is the conflic

arXiv:2604.05552v2 Announce Type: replace-cross Abstract: Large Language Models demonstrate outstanding performance in many language tasks but still face fundamental challenges in managing the non-lin

arXiv:2604.15561v1 Announce Type: cross Abstract: Reported chest CT segmentation performance can be strongly inflated when train and test partitions mix slices from the same study. We present CTSCAN,

arXiv:2604.15555v1 Announce Type: new Abstract: Chest X-ray (CXR) interpretation is hindered by the long-tailed distribution of pathologies and the open-world nature of clinical environments. Existing

arXiv:2604.15593v1 Announce Type: cross Abstract: Large language models compress heterogeneous knowledge into a single parameter space, allowing facts from different domains to interfere during genera

arXiv:2406.14294v3 Announce Type: replace-cross Abstract: Discrete audio tokens have recently gained considerable attention for their potential to bridge audio and language processing, enabling multim

dear god lol - new kimi model is a fucking beast. GPT 5.4 level coding, 76% cheaper than opus 4.7 and 100% open source / free to use, i mean look at this: > kimi k2.6 can code continuously for 12 hour

arXiv:2604.16099v1 Announce Type: new Abstract: Tables condense key transactional and administrative information into compact layouts, but practical extraction requires more than text recognition: sys

arXiv:2604.15866v1 Announce Type: cross Abstract: Large language models (LLMs) have advanced information extraction (IE) by enabling zero-shot and few-shot named entity recognition (NER), yet their ge

arXiv:2604.16256v1 Announce Type: cross Abstract: Reasoning in vision-language models (VLMs) has recently attracted significant attention due to its broad applicability across diverse downstream tasks

arXiv:2604.15851v1 Announce Type: cross Abstract: Differential privacy (DP) has a wide range of applications for protecting data privacy, but designing and verifying DP algorithms requires expert-leve

arXiv:2512.23421v3 Announce Type: replace Abstract: World models have become crucial for autonomous driving, as they learn how scenarios evolve over time to address the long-tail challenges of the rea

arXiv:2509.09530v2 Announce Type: replace Abstract: Three-dimensional ultrasound (US) offers many clinical advantages over conventional 2D imaging, yet its widespread adoption is limited by the cost a

arXiv:2512.17052v4 Announce Type: replace Abstract: Function calling agents powered by Large Language Models (LLMs) select external tools to automate complex tasks. On-device agents typically use a re

Earlier this year Yann LeCun left Meta because Mark Zuckerberg wouldn't bet the company on JEPA. Last week his group dropped the first JEPA that actually trains end-to-end from raw pixels. 15 million

arXiv:2604.15822v1 Announce Type: cross Abstract: Automated classification of electrocardiogram (ECG) signals is a useful tool for diagnosing and monitoring cardiovascular diseases. This study compare