Search: “models”

arXiv:2602.04163v2 Announce Type: replace Abstract: Large language model inference is often bounded by memory footprint and bandwidth in resource-constrained deployments, making quantization fundament

arXiv:2605.15995v1 Announce Type: cross Abstract: Learning latent representations from complex data is central to modern machine learning, spanning temporal, multimodal, and partially observed systems

arXiv:2605.16113v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved unprecedented success due to their exceptional generative capabilities. However, because they depend on kno

arXiv:2605.15706v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existi

arXiv:2605.15855v1 Announce Type: new Abstract: Despite strong image-generation performance, diffusion models' reconstruction objectives limit alignment with human preferences. RL enables such alignme

arXiv:2605.15803v1 Announce Type: new Abstract: Recent advancements have established Reinforcement Learning (RL) as a pivotal paradigm for aligning generative models with human intent. However, group-

arXiv:2506.22440v2 Announce Type: replace-cross Abstract: This paper introduces the Generality-Accuracy-Simplicity (GAS) framework to analyze how large language models (LLMs) are reshaping organizatio

I believe on-prem and local AI - based on @huggingface open-source models - will be an important answer to the GPU shortages this year (because they are cheaper, faster, safer than cloud APIs)! Great

arXiv:2605.15822v1 Announce Type: new Abstract: Score-based generative models are trained in high-dimensional ambient spaces, yet many data distributions are supported on low-dimensional nonlinear str

Introducing Agora-1, a multi-agent world model. Multiple participants—human or AI—can now interact inside the same world simulation, all in real-time. Try our playable research preview today, with Ago

LangSmith Engine automates the full agent fix loop — detecting failures, diagnosing causes and drafting PRs. But multi-model enterprises say a neutral observability layer still wins. http://venturebea

arXiv:2605.15831v1 Announce Type: cross Abstract: Autoregressive music generation depends strongly on the audio tokenizer. Existing high-fidelity codecs often use residual multi-codebook quantization,

arXiv:2605.16107v1 Announce Type: new Abstract: Machine-generated texts (MGTs) pose risks such as disinformation and phishing, underscoring the need for reliable detection. Metric-based methods, which

okay maybe it's a good time? We have a small colbert model trained at pplx, it is a continue-training of pplx-embed-0.6b, so native multilingual, just made it open and added a section how to use MaxSi

arXiv:2605.15301v1 Announce Type: new Abstract: Large language models (LLMs) still struggle with the rigorous reasoning demands of hard competitive programming. While recent multi-agent frameworks att

Tesla Model Y's powered rear seats and trunk are equipped with automatic obstruction detection that causes them to automatically reverse and pop back up if an obstruction is detected during operation,

Eleanor Olcott / Financial Times: Developers say Chinese AI labs lead US rivals in video generation, as ByteDance and Kuaishou train models on vast short-form video libraries from their own apps — Chi

Alison Weissbrot / Adweek: Publicis agrees to acquire LiveRamp, which allows companies to share and build new data sets and models that can power agentic frameworks, for 2.2B in cash — Publicis Groupe

Rebecca Bellan / TechCrunch: A profile of AI video generation startup Runway, which is training models directly on observational data, is now valued at 5.3B, and added 40M in ARR in Q2 — Every major A

AI teams shouldn’t have to choose between expensive object storage and painful git workflows. @huggingface Storage is built for model weights, datasets, checkpoints and artifacts: - simple per-TB pric

arXiv:2605.14773v1 Announce Type: cross Abstract: Data selection accelerates training by identifying representative training data while preserving model performance. However, existing methods mainly f

BREAKING: The results are in for Slides Arena... @AnthropicAI and @Zai_org models continue to lead the way in soft-verifiable domains 1st: Opus 4.7 by @AnthropicAI 2nd: Opus 4.7 (Thinking) by @Anthrop

arXiv:2605.15077v1 Announce Type: cross Abstract: Function calling, also known as tool use, is a core capability of modern LLM agents but is typically constrained by synchronous execution semantics. U

arXiv:2605.14227v1 Announce Type: cross Abstract: Accurate disease trajectory prediction is critical for early intervention, resource allocation, and improving long-term outcomes. While electronic hea

arXiv:2605.14535v1 Announce Type: new Abstract: The increased use of Large Language Models (LLMs) in geography raises substantial questions about the safety of integrating these tools across a wide ra

arXiv:2603.21250v2 Announce Type: replace Abstract: Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former

arXiv:2605.14267v1 Announce Type: cross Abstract: Diffusion models (DMs) have exhibited remarkable efficacy in various image restoration tasks. However, existing approaches typically operate within th

Julie Bort / TechCrunch: In a viral X post that parodies the old Mac vs. PC commercials, General Catalyst posted a “VC vs GC” video, with the VC apparently modeled after Marc Andreessen — One of the m

arXiv:2605.14935v1 Announce Type: new Abstract: We present MSCoT, a multi-scale, coarse-to-fine model for test-time human motion synthesis and control. Unlike recent approaches that rely on multiple i

arXiv:2509.22151v3 Announce Type: replace Abstract: Material node graphs are programs that generate the 2D channels of procedural materials, including geometry such as roughness and displacement maps,

arXiv:2605.14683v1 Announce Type: new Abstract: High-resolution seafloor mapping necessitates stable and precise positioning for underwater robots. This paper introduces a novel mathematical model for

arXiv:2602.04657v3 Announce Type: replace Abstract: Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most ex

We’re releasing a 30B-A3B reasoning model that reaches gold-medal level across both physics and math Olympiad evaluations: IPhO directly, and IMO/USAMO with test-time self-verification and refinement.

arXiv:2605.13687v1 Announce Type: cross Abstract: We introduce a family of synthetic languages with hierarchical structure -- generated by a broadcast process on trees -- for which the role of context

Are scaling laws finally working for time series foundation models? Today, @datadoghq is releasing Toto 2.0 weights in Apache 2.0 on @huggingface. It's a family of open-weights TSFMs from 4M to 2.5B p

arXiv:2605.13450v1 Announce Type: new Abstract: Measuring the creativity of large language models (LLMs) is essential for designing methods that can improve creativity and for enhancing our scientific

Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements to caching for faster inference overall. Turn on Developer Mod

arXiv:2605.13178v1 Announce Type: cross Abstract: In large vision-language models, visual tokens typically constitute the majority of input tokens, leading to substantial computational overhead. To ad

arXiv:2510.08992v3 Announce Type: replace Abstract: While researchers have made significant progress in enabling large language models (LLMs) to perform multi-step planning, LLMs struggle to ensure th

Dear AI labs, A neverending black and white kanban board modeled after Jira (no offense) is not what we want as the future of work. Give me flexibility. Give me delight. Give me color. Please create t

arXiv:2605.12702v1 Announce Type: new Abstract: General-purpose safety benchmarks for large language models do not adequately evaluate disability-related harms. We introduce DisaBench: a taxonomy of t

arXiv:2605.13156v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in bridging visual perception and natural language understanding, enabling a wid

arXiv:2406.13619v4 Announce Type: replace-cross Abstract: This paper develops a generative model by minimizing the second-order Wasserstein loss (the W_2 loss) through a distribution-dependent ordinar

arXiv:2605.13375v1 Announce Type: cross Abstract: In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware

arXiv:2605.13080v1 Announce Type: new Abstract: When humans describe a visual scene, they do not process the entire image uniformly; instead, they selectively fixate on regions relevant to their inten

arXiv:2605.13711v1 Announce Type: new Abstract: Multimodal irregular time series (MITS) consist of asynchronous and irregularly sampled observations from heterogeneous numerical and textual channels.