Search: “inference”

Model Developer: NVIDIA Corporation Model Development: Fine-tuned from NVIDIA-Nemotron-3-Ultra-550B-A55B What is Nemotron? NVIDIA Nemotron™ is a family of open models with open weights, training data,

ok i think i finally figured out why alignment has gone basically nowhere after 15 years and several billion dollars. the problem is hard sure. but have you met the people in charge of it 1) the leade

arXiv:2609.31185v1 Announce Type: new Abstract: Effective wind gust rejection and stable hovering are critical for the outdoor operation of autonomous drones. However, existing gust rejection methods

arXiv:2609.30946v1 Announce Type: cross Abstract: Action-conditioned video world models aim to predict scene evolution under different actions, a capability that is essential for reliable planning, de

OpenAI’s so reckless, “It is like if in … Jurassic Park they would have let all the dinosaurs roam free not only on the island but on a populated continent” What is so bad here is that they should hav

arXiv:2609.30749v1 Announce Type: new Abstract: Data Science Code Translation (DSCT) is the process of converting code between data science libraries while preserving functional equivalence and enabli

arXiv:2609.30337v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates knowledge obsolescence and factual hallucination in large language models by introducing external context

Personal agents gone wrong. As we embrace more personal agents to carry out personalized tasks in the real world, interesting dynamics and behaviors will emerge. I think personal agents as they stand

arXiv:2609.31135v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to localize the spatio-temporal tube in a video corresponding to a natural language query. While recent me

arXiv:2609.31468v1 Announce Type: cross Abstract: LLMs increasingly act as purchasing agents, which makes the LLM, not the user, the one choosing among the options that satisfy a request; its preferen

arXiv:2609.31505v1 Announce Type: new Abstract: Despite the growing capabilities of large language models (LLMs), prompt design remains largely heuristic and ad hoc. This project will explore extit{pr

arXiv:2609.30465v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models activate few experts per token but store the full expert pool. Expert pruning reduces this storage burden; at a fixed

arXiv:2609.31160v1 Announce Type: cross Abstract: Vessel segmentation in medical images is essential for many clinical tasks, ranging from diagnosis to treatment planning. However, it remains challeng

arXiv:2609.31337v1 Announce Type: new Abstract: Building a robotic manipulation system requires connecting perception, planning, and control through carefully designed representations and interfaces.

arXiv:2609.31013v1 Announce Type: new Abstract: Researchers increasingly use generative large language models (LLMs) to convert corporate text into empirical variables. We examine the extent to which

arXiv:2609.31201v1 Announce Type: new Abstract: Scaling studies typically represent training data by a single count of samples. For hierarchically and spatially structured data, however, the same numb

arXiv:2609.30987v1 Announce Type: new Abstract: Self-supervised monocular depth estimation (MDE) enables depth prediction from monocular images without requiring ground-truth supervision, making it at

arXiv:2609.30294v1 Announce Type: cross Abstract: Scientific presentations are more than summaries of research papers. They need to present the work in a coherent sequence, explain the main ideas clea

arXiv:2609.30299v1 Announce Type: new Abstract: Representation quality is a central determinant of PINNs' performance, yet standard training leaves representations to emerge implicitly while fitting t

Today, we’re excited to announce the general availability of our next-generation Storage-optimized Z4D machine series in Google Compute Engine with both Virtual Machine (VM) and bare-metal instances.

arXiv:2609.30682v1 Announce Type: new Abstract: Self-supervised pre-training with Vision Transformers, including Masked Autoencoders (MAE), is difficult to apply to gigapixel scientific images. Random

arXiv:2609.31024v1 Announce Type: cross Abstract: Sound matching can be formulated as optimizing synthesizer parameters against an audio-domain objective. However, objectives derived from generic audi

arXiv:2609.31341v1 Announce Type: new Abstract: Whether an information extraction pipeline should process page images or parsed text depends on the document, and the answer flips across the layout spe

arXiv:2609.31371v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising performance in log anomaly detection, yet how their adaptation strategies, architectures, and d

arXiv:2609.31005v1 Announce Type: new Abstract: Open-vocabulary 3D maps enable robots to reason about previously unknown environments using natural language. However, existing systems typically segmen

arXiv:2609.30924v1 Announce Type: new Abstract: Accurate and efficient pronunciation transcription is essential for preparing text-to-speech training data at scale. Existing approaches have different

arXiv:2609.31357v1 Announce Type: new Abstract: To be able to perform inspection or digitization tasks, mobile robots on construction sites must be able to localize themselves reliably with respect to

arXiv:2609.31463v1 Announce Type: cross Abstract: Infant movement analysis provides valuable biomarkers for the early identification of neurodevelopmental disorders. Recent advances in deep learning h

arXiv:2609.30709v1 Announce Type: cross Abstract: Traffic signal control (TSC) is essential for mitigating urban congestion. Recent advances in vision-language models (VLMs) enable richer interpretati

arXiv:2609.30719v1 Announce Type: cross Abstract: Contemporary on-chain artificial intelligence (AI) encounters an intractable Von Neumann memory and latency wall. Storing static floating-point neural

arXiv:2609.31050v1 Announce Type: new Abstract: Efficient video generation requires reducing the quadratic cost of self-attention over long spatio-temporal token sequences. Existing efficient-attentio

Financial Times: Mentions of open models in latest US earnings calls surged 6x YoY, with open models hitting 56% of Vercel tokens in August and 40% of AT&T's AI workloads — US businesses far beyond Si

🛠️ MiMo-V2.6 update: tool-call repetition, diagnosed & fixed. After the MiMo-V2.6 series models launched, we noticed them sometimes repeating identical or highly similar tool calls — burning context a

Been doing a bunch of vibe coding lately. Had my agents host a private WoW server for me, then built out a web browser client so you can play without installing the game and it has mobile controls. Af

an implicit concession that they cannot control their models. Notable new disclosures from OpenAI that shouldn't get lost in all the other news. Of particular interest (and seems sensible!): '~all inf

And the incidents apparently continue. It is worth noting how much of this is agents trying to accomplish their goals during testing by reward hacking (which sometimes seems to include actual hacking)

i don’t get it fully but this looks cool We achieved a breakthrough at BTL. AI models are very linear. They think in one direction at a time, and when they're wrong they scramble and start again. For

Micha wrote “one of our models was able to gain unauthorized access to the internet during RL training” I love the use of the passive voice. Tis a subtle way to say “we humans at @OpenAI are essential

On my M5 Pro 64GB I can comfortably work in an agentic setup with the Qwen3.8 27B model in good quality (Unsloth UD-Q4_K_XL) at a decent speed of 50 t/s. Splash combines optimized kernels, excellent s

arXiv:2512.06607v2 Announce Type: replace-cross Abstract: Applying LLMs to predictive tasks in finance is challenging due to look-ahead bias resulting from their training on long time-series data. Thi

arXiv:2609.30205v1 Announce Type: new Abstract: Large language model (LLM)-based clinical assistants are increasingly being integrated into electronic health record (EHR) systems, transforming how cli

arXiv:2609.29084v1 Announce Type: new Abstract: Developing optimized machine-learning algorithms for edge devices with limited computational and memory resources is challenging, time-consuming, and hi

arXiv:2609.28476v1 Announce Type: cross Abstract: While a number of methods exist for counting pedestrians in street-view imagery, these mostly ignore the social dimensions of pedestrian activity. A s

arXiv:2609.30250v1 Announce Type: new Abstract: Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express

arXiv:2609.28703v1 Announce Type: cross Abstract: Hate speech on social media poses serious risks to social harmony, mental well-being, and public safety, making its timely and accurate detection esse

arXiv:2609.29191v1 Announce Type: new Abstract: Sensitive information is defined by domain and intent, not a universal category, yet redaction systems such as privacy filters and named-entity recogniz