Search: “models”

arXiv:2412.07041v4 Announce Type: replace-cross Abstract: Recovering incomplete multidimensional tensor-structured data is a fundamental task in many real-world applications. Smoothness-constrained lo

arXiv:2607.20146v1 Announce Type: new Abstract: Large language models often align with users' beliefs at the expense of factual accuracy, a behavior known as sycophancy. Prior mechanistic studies larg

arXiv:2607.18955v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) provides reliable outcome supervision for language model reasoning, but a scalar traject

arXiv:2607.18325v1 Announce Type: new Abstract: Modern safety-critical systems increasingly rely on human-robot interaction to reduce disaster risk and support decision-making during emergencies. Visi

arXiv:2607.19398v1 Announce Type: new Abstract: Multi-entity compositional questions pose significant challenges to existing retrieval-augmented language models. Conventional methods fall into a dilem

https://preview.redd.it/u8alj38wr0fh1.png?width=1860&format=png&auto=webp&s=3578776c60d9548a135a018702f44d0fddedd4b0 Little side project I'm doing so I can easily transfer any model I want fast to my

I wrote the latest of my occasional guides to which AI to use right now for non-experts who want to get stuff done. The agentic systems available to everyone are getting extremely powerful (even as th

arXiv:2607.19490v1 Announce Type: cross Abstract: Peer-to-peer distributed inference executes a Large Language Model (LLM) on pooled consumer hardware by spreading its layers across many nodes. Every

arXiv:2607.20321v1 Announce Type: cross Abstract: Neural surrogates are widely used in scientific machine learning for fast prediction of three-dimensional (3D) thermo-fluid fields. However, generatin

arXiv:2607.19811v1 Announce Type: new Abstract: The Segment Anything Model 2 (SAM2) has advanced temporal promptable segmentation, yet its deployment remains hindered by heavy memory cross-attention o

arXiv:2501.14546v2 Announce Type: replace-cross Abstract: This paper investigates the novel application of Large Language Models (LLMs) with vision capabilities to analyze satellite imagery for villag

arXiv:2607.20153v1 Announce Type: new Abstract: We study Gaussian averaging as a smooth surrogate for quantized neural models. Under bounded local oscillation, we derive a local dimension-dependent bo

arXiv:2607.19426v1 Announce Type: cross Abstract: Single-cell datasets are increasingly costly to store, audit, and reuse for model training. Dimensionality reduction and dataset distillation can redu

arXiv:2607.19371v1 Announce Type: new Abstract: Large language model (LLM)-based Socratic tutors increasingly guide students through multi-turn questioning, but they can suffer from scaffolding collap

Mobile app security company NowSecure Inc. today introduced a set of artificial intelligence-native features for its testing platform, including a chat assistant, a Model Context Protocol server and n

arXiv:2607.19806v1 Announce Type: cross Abstract: Activation steering provides a lightweight mechanism for controlling large language models at inference time, but steering vectors can have unintended

arXiv:2607.20389v1 Announce Type: new Abstract: Video captioning requires fine-grained spatio-temporal understanding of videos, including spatial perception of where objects are located and temporal p

arXiv:2607.20385v1 Announce Type: cross Abstract: Optical Character Recognition (OCR) for Persian remains substantially less mature than for Latin-script languages despite Persian being spoken by more

arXiv:2603.28282v2 Announce Type: replace-cross Abstract: Edge AI systems increasingly rely on federated learning to train perception models in distributed, privacy-preserving, and resource-constraine

arXiv:2607.18773v1 Announce Type: new Abstract: Accurate skin lesion classification can benefit from lesion segmentation masks, but requiring masks or an auxiliary segmentation model during inference

arXiv:2607.16195v2 Announce Type: replace Abstract: We identify a structured confound in Reinforcement Learning from Human Feedback (RLHF). Pairwise preference labels are intended to reflect the compa

arXiv:2607.19376v1 Announce Type: cross Abstract: Machine learning models trained on biochemical data are routinely evaluated using splits that fail to account for relational structure, causing inform

arXiv:2607.15774v2 Announce Type: replace-cross Abstract: Explainable AI (XAI) for time series has seen significant algorithmic growth, but its utility in providing measurable performance gains for do

arXiv:2510.16834v3 Announce Type: replace-cross Abstract: We present Schrodinger Bridge Mamba (SBM), a novel model for efficient speech enhancement by integrating the Schrodinger Bridge (SB) training

arXiv:2607.18508v1 Announce Type: new Abstract: Preference over model-generated emotion descriptions is emerging as a standard evaluation metric for multimodal emotion understanding, exemplified by th

arXiv:2607.19535v2 Announce Type: new Abstract: Incorrect disposal can contaminate campus recycling streams, and a bin-mounted camera could provide feedback as an item is discarded. We evaluated wheth

arXiv:2607.16824v2 Announce Type: replace Abstract: Attention-based models often develop attention sinks, where a small number of tokens repeatedly attract attention and accumulate unusually large act

arXiv:2607.19390v1 Announce Type: new Abstract: A recent report finds that orthogonalizing the mLSTM memory matrix at read time (five Newton-Schulz iterations, trained through) substantially improves

arXiv:2607.19994v2 Announce Type: new Abstract: Sentinel-2 imagery offers open access, global coverage, and frequent revisit times, making it attractive for practical building mapping at scale; howeve

arXiv:2504.03707v2 Announce Type: replace-cross Abstract: Emotion recognition is crucial for advancing mental health, healthcare, and technologies such as brain-computer interfaces. EEG-based models,

arXiv:2607.19595v1 Announce Type: cross Abstract: Large language model (LLM) agents are vulnerable to security risks, such as prompt injection attacks from untrusted context that manipulate downstream

arXiv:2607.19523v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is widely used to adapt large language models to downstream tasks, but its effect on behavioral diversity in sequential dec

arXiv:2607.19802v1 Announce Type: cross Abstract: Sequential recommendation (SR) models capture continuously observed behavior, but a returning user may have no interactions for months or years. We de

Are structured outputs in agents always good? This paper suggests that you might have to take a closer look. Your product's structured output surface is measurably more homogeneous than the chat surfa

Copilot now bills usage at listed API rates. Compare direct model access with the coding workflow, policy, and harness work around it. The post Copilot vs. raw API access: What are you actually paying

TESSERA leverages Vultr’s cloud GPU infrastructure, specifically AMD Instinct™ GPUs, to process satellite data at planetary scale. By integrating foundation‑model AI, TESSERA accelerates Earth‑observa

OpenAI admitted that an agent powered by its GPT‑5.6 Sol and a pre‑release model escaped a sandboxed test environment and gained unauthorized access to Hugging Face’s servers while attempting to solve

A federal judge has signed off on Anthropic's 1.5 billion class action settlement with authors who accused the company of training its AI models on copyrighted books, as reported earlier by Reuters. I

AI has entered the gigascale era. The world’s most advanced AI factories are bringing together hundreds of thousands of GPUs and CPUs to train frontier models, power agentic AI and generate intelligen

The NVIDIA GB300 NVL72 platform set a world record by delivering 1,648 TFLOPs per GPU during the pre‑training of DeepSeek‑V3 671B, a mixture‑of‑experts (MoE) model. This achievement leveraged fifth‑ge

Gizmo is a simulation-authoring agent that converts textual descriptions and reference images into structured, editable 3D scenes tailored for robotics workflows. It was publicly released as a beta on

this is important and true. and if you don’t understand it you don’t really understand what’s going on. @GaryMarcus Yes — model makers quietly went from benchmarking LLMs to benchmarking LLM+harness,

We had guessed reward seeking might increase over the course of capabilities-focused RL training, but had no way of measuring it until now. We’re continuing to collaborate with Apollo Research to impr

// Global Workspace in LLMs // arXiv paper for the popular J-space work from Anthropic. (bookmark it) The short recap: If you build on chain-of-thought or steering vectors, this work provides a mechan

arXiv:2603.21393v2 Announce Type: replace Abstract: The widespread use of AI and ML models in sensitive areas raises significant concerns about fairness. While the research community has introduced va

arXiv:2607.13237v1 Announce Type: new Abstract: Precise spatial-temporal annotation of laparoscopic videos is time-consuming and requires expert knowledge. We propose a human-in-the-loop knowledge acq