Search: “model-releases”

arXiv:2605.11374v1 Announce Type: cross Abstract: Test-time compute is widely believed to benefit only large reasoning models. We show it also helps small embedding models. Most modern embedding check

The future of AI is agent-native. Excited to kick off this journey together with Hermes Agent and the @NousResearch community. Qwen 3.6 Plus is now FREE for a limited time on Nous Portal — give it a t

Databases have introduced new AI-powered SQL functions which take natural language instructions as input and are evaluated using LLMs. They leverage the power of LLMs to answer new kinds of queries: W

arXiv:2605.11157v1 Announce Type: cross Abstract: We study proportional representation in the temporal voting model, where collective decisions are made repeatedly over time over a fixed horizon. Prio

arXiv:2605.11205v1 Announce Type: new Abstract: Benchmark evaluation across AI and safety-critical domains overwhelmingly relies on simple averaging. We demonstrate that this practice produces substan

The UK’s state AI Security iIstitute findings: 1) Mythos is a big gain in cyber capabilities. But so is GPT-5.5 2) It is hard to establish an upper bound on Mythos/GPT-5.5, which appear to be limited

This is misleading. This policy redefines the term 'interactive' to mean 'using an Anthropic front-end'. If you use `claude -p` or Agent SDK to do something interactively, it now uses credits, not you

This jackass fought hard to remain NASA Administrator. SCOOP: I obtained a pitch deck in which the entity that paid for Transportation Sec’y Duffy’s new reality show outlined different partner levels

arXiv:2605.11574v1 Announce Type: new Abstract: The literature on how large language models handle conflict between their training knowledge and a contradicting document presents a persistent empirica

Aisha Malik / TechCrunch: TikTok launches TikTok GO in the US for users to book hotels, attractions, and experiences directly in the app, partnering with Booking.com, Expedia, and others — TikTok anno

arXiv:2605.11473v1 Announce Type: cross Abstract: Soft Actor-Critic (SAC) and its variants dominate Multi-Task Reinforcement Learning (MTRL) due to their off-policy sample efficiency, while on-policy

arXiv:2605.12391v1 Announce Type: cross Abstract: We present a novel method for extracting moving objects from TESS data using machine learning. Our approach uses two stacked 3D U-Nets with skip conne

arXiv:2605.11735v1 Announce Type: new Abstract: The efficient operation of modern cellular networks hinges on the accurate analysis of spatio-temporal traffic data. Mastering these patterns is essenti

arXiv:2605.12237v1 Announce Type: new Abstract: Vision-Language Models (VLMs) increasingly operate on ultra-high-resolution (UHR) Earth observation imagery, yet they remain vulnerable to a severe scal

arXiv:2511.18152v3 Announce Type: replace Abstract: Deep unfolding networks (DUNs) combine the interpretability of model-based methods with the learning ability of deep networks, yet remain limited fo

arXiv:2605.11634v1 Announce Type: new Abstract: Although Vision Language Models (VLMs) have seen tremendous progress across all kinds of use cases, they still fall behind in answering questions regard

arXiv:2605.11782v1 Announce Type: new Abstract: Visual impairment affects hundreds of millions of people worldwide, severely limiting their ability to navigate urban environments safely and independen

arXiv:2605.11334v1 Announce Type: cross Abstract: LLM-as-Judge systems are widely deployed for automated evaluation, yet practitioners lack reliable methods to know when a judge's verdict should be tr

arXiv:2605.11864v1 Announce Type: cross Abstract: Listwise reranking is a key yet computationally expensive component in vision-centric retrieval and multimodal retrieval-augmented generation (M-RAG)

arXiv:2603.11383v2 Announce Type: replace Abstract: Teleoperation of low-cost robotic manipulators remains challenging due to the difficulty of retargeting human hand motion to robot joint commands. W

arXiv:2605.11307v1 Announce Type: new Abstract: Image-to-code generation tests whether a vision-language model (VLM) can recover the structure of an image enough to express it as executable code. Exis

We built SmithDB: the database purpose built for agent observability workloads that now powers many parts of LangSmith. Agent observability presents a challenging data problem. Agent traces can contai

🎉 We published a new AI safety study: shopping agents fall for whimsical attacks and lose money. A whimsical attack is an absurd scenario a human would never try on another human. In one run, GPT-5.1

arXiv:2605.11654v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL), which matches an oblique drone view to a geo-referenced satellite tile, has emerged as a key alternative for autonom

arXiv:2605.11963v1 Announce Type: new Abstract: This paper examines what it means for a medical AI system to be right by grounding the question in a specific clinical context: the automatic classifica

When you want to move from single agent SQLite on something like QMD, PostgreSQL is a great choice for multi agent and production quality, but not as snappy. So we made it much more snappy with BM25 &

💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter most in long-context inference: → KV-cache pressure during de

arXiv:2605.11696v1 Announce Type: new Abstract: Recent single-image relighting methods, powered by advanced generative models, have achieved impressive photorealism on synthetic benchmarks. However, t

DeepSeek-v4 Flash through Ollama is currently available as a cloud model, where Ollama's CLI sends API calls to Ollama's hosted version rather than running locally . Local support for DeepSeek V4 Flas

arXiv:2605.11521v1 Announce Type: new Abstract: Autonomous driving and intelligent transportation systems remain vulnerable under extreme weather. The U.S. Federal Highway Administration reports that

arXiv:2605.11906v1 Announce Type: new Abstract: Preference optimization has become an important post-training paradigm for improving the reasoning abilities of large language models. Existing methods

arXiv:2605.08600v1 Announce Type: new Abstract: We present a new publicly available corpus of 100,502 movie reviews from Kazakhstan collected from kino.kz, spanning 2001-2025 and covering 4,943 unique

arXiv:2605.10204v1 Announce Type: new Abstract: Accurate 3D reconstruction of objects with reflective, transparent, or low-texture surfaces still remains notoriously challenging. Such materials often

arXiv:2605.09483v1 Announce Type: cross Abstract: In this (work in progress) paper, we present Bounded Pragmatic Listener (or BPL), a cognitively grounded Bayesian framework for modelling susceptibili

arXiv:2605.09121v1 Announce Type: cross Abstract: Agents built on large language models (LLMs) rely on a range of reliability techniques, including retry, majority voting, and self-consistency, that h

arXiv:2605.08517v1 Announce Type: cross Abstract: We describe an approach for estimating the statistical risk of deep networks that contain a mix of learned and known operators. Building on the maxima

arXiv:2605.09515v1 Announce Type: new Abstract: Large language models rely on multihead attention, but interactions among heads remain poorly understood. We apply the Game Theoretic Free Energy Princi

arXiv:2605.09011v1 Announce Type: cross Abstract: We investigate the geometry of predictive information across the layers of large language models (LLMs). We repurpose representation lenses-learned af

arXiv:2605.08436v1 Announce Type: cross Abstract: We introduce a meshfree exterior calculus (MEEC) for learning structure-preserving descriptions of physics on point clouds, and use it to build MEEC-N

arXiv:2512.06427v2 Announce Type: replace Abstract: Proper initialisation strategy is of primary importance to mitigate gradient explosion or vanishing when training neural networks. Yet, the impact o

arXiv:2605.09032v1 Announce Type: cross Abstract: Reliable short horizon forecasting of solar and wind generation is a structural prerequisite of any modern power system yet most published forecasters

arXiv:2605.10076v1 Announce Type: cross Abstract: Generative (diffusion) priors demonstrate remarkable performance in addressing inverse problems in imaging. Yet, for scientific and medical imaging, i

A startup wants to pull magnesium from seawater without torching the environment. Another wants to take small language models to the podium for enterprise customers. Today @jason and @alex sat down wi

arXiv:2512.17593v3 Announce Type: replace Abstract: In this paper we consider the limiting case of neural networks (NNs) architectures when the number of neurons in each hidden layer and the number of

arXiv:2605.09755v1 Announce Type: cross Abstract: The power method is one of the most fundamental tools for extracting top principal components from data through low-rank matrix approximation. Yet, wh

arXiv:2605.10575v1 Announce Type: cross Abstract: Safe fine-tuning defenses are often endorsed on the basis of a held-out gap reduction, but the same reduction can come from sampling noise, subject ar