All entries

arXiv:2609.03080v1 Announce Type: new Abstract: Segmenting a new biomedical dataset usually means a domain-specific model trained on substantial annotation, or a foundation model steered at inference

Having launched an artificial intelligence-based virtual assistant in the spring, Experian plc is driving AI deeper into its operations with a commercial agent-based platform designed to bring its ris

arXiv:2405.07338v2 Announce Type: replace-cross Abstract: Early detection of vision-threatening conditions such as diabetic retinopathy, glaucoma, and age-related macular degeneration depends on retin

arXiv:2609.03391v1 Announce Type: cross Abstract: Contrastive language-image learning (CLIP) has become a key paradigm for remote sensing vision-language understanding. However, existing remote sensin

arXiv:2609.03662v1 Announce Type: new Abstract: Recent unlearning methods (e.g. NPO, DPO, LUNAR) make use of refusal alignment to suppress forgotten data. However, it has been shown that refusal respo

arXiv:2603.21304v3 Announce Type: replace Abstract: Feed-forward 3D Gaussian Splatting methods enable single-pass reconstruction and real-time rendering. However, they typically adopt rigid pixel-to-G

arXiv:2609.03611v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly used to evaluate robot manipulation outcomes, but existing benchmarks offer limited evidence of cross-d

arXiv:2609.03147v1 Announce Type: cross Abstract: Learning-based schedulers have been proposed to provide real-time user, target, and access point (AP) association in distributed cell-free integrated

arXiv:2609.03535v1 Announce Type: new Abstract: Lesion segmentation in medical images plays a critical role in clinical diagnosis and treatment planning. Despite significant advances, lesion segmentat

arXiv:2609.03705v1 Announce Type: new Abstract: In this paper we study linear non-Gaussian acyclic models (LiNGAM) when used in federated environments. These causal models allow one to go beyond Marko

arXiv:2602.10870v2 Announce Type: replace-cross Abstract: Federated Learning (FL) enables multiple parties to collaboratively train machine learning models without sharing raw data. However, before tr

Jonathan Randles / Bloomberg: Filing: AI training data startup Micro1 offers to pay 12.5M for Spirit Airlines' data; the offer faces hurdles as Spirit already has a 10M deal with Google — An artificia

arXiv:2609.03740v1 Announce Type: new Abstract: Mirrors are common in real-world images, yet producing geometrically consistent reflections with generative models remains challenging. Unlike most obje

arXiv:2609.03960v1 Announce Type: new Abstract: Banks need conversational systems that can answer product questions, assist customers with account-related requests, and operate safely within strict op

arXiv:2510.01721v4 Announce Type: replace Abstract: Distributionally robust reinforcement learning seeks policies that remain effective when the deployment environment differs from the one that genera

arXiv:2609.03930v1 Announce Type: new Abstract: Existing research has repeatedly observed the tendency for English loanwords to cluster in the masculine gender across different recipient languages, ye

arXiv:2609.03563v1 Announce Type: new Abstract: We present FlashRender, a few-step generative rendering framework that retakes a source video along a target camera trajectory in seconds. We identify s

arXiv:2601.22376v2 Announce Type: replace Abstract: High-definition (HD) maps provide essential semantic information about road structures for autonomous driving, but existing HD map construction meth

arXiv:2609.03844v1 Announce Type: cross Abstract: We introduce Stateless Bernoulli Watermarking (SBW), a new statistical watermark for Large Language Models that determines green list membership throu

arXiv:2609.03241v1 Announce Type: cross Abstract: A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal verifiers provide reliable yet sparse superv

arXiv:2609.04021v1 Announce Type: new Abstract: Evaluating large language models (LLMs) in safety-critical, physics-governed environments requires more than accuracy-based metrics, because predictions

arXiv:2609.03222v1 Announce Type: new Abstract: Certifiable methods have arisen as a means to guarantee global optimality of solutions to non-convex problems using convex semidefinite programming (SDP

For how much I use AI and automation, you'd THINK I run 100% of my business through Codex or Claude Code or Slack. But I still use native apps. I talk to several people who brag that 'they don't even

for the first time in a year, @OpenAI's model launch has been better received than a Claude launch. https://www.latent.space/p/ainews-gpt-6-astra-openais-biggest this is a huge upset that we had previ

arXiv:2609.03384v1 Announce Type: new Abstract: In-Context Segmentation (ICS) aims to precisely segment arbitrary semantic concepts, such as objects or parts, given one or a few annotated visual exemp

arXiv:2609.04158v1 Announce Type: cross Abstract: This paper presents an energy-based controller for a multiagent robotic system designed to achieve and maintain a specific formation while moving on a

arXiv:2609.03331v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in multi-turn settings where users may describe visual content with incorrect assumptions. Yet e

arXiv:2609.03370v1 Announce Type: new Abstract: In frame semantics, sentence comprehension is assumed to proceed by relating lexical meaning to background knowledge called semantic frames, thereby ena

arXiv:2609.03807v1 Announce Type: cross Abstract: A free pause token gives a language model extra compute to form each next-token prediction (as a pause, or thinking, token does) but carries that comp

arXiv:2609.03340v1 Announce Type: new Abstract: Distributed LLM-agent teams can read the latest shared facts and still act on an obsolete plan. A planner may derive an action from requirement r_3, ano

arXiv:2609.02948v1 Announce Type: cross Abstract: Predicting the thermodynamic properties of an alloy requires sampling its configurations across many chemical conditions and recovering free energies

arXiv:2609.04166v1 Announce Type: new Abstract: Research and news coverage of language-model deception increasingly attributes human-like mental-state concepts to language models. Such claims can blur

arXiv:2609.02984v1 Announce Type: new Abstract: The conventional approach to machine learning, that is, collecting data, training models, and performing inference in a single location, faces fundament

arXiv:2609.03763v1 Announce Type: new Abstract: Accurate cloud-cover forecasts are important for temperature prediction, radiation forecasting, and solar-power operations. Short-range forecasting meth

arXiv:2609.03801v1 Announce Type: new Abstract: We study the ordered Bernoulli-word kernel f(p,n,k)=p^k(1-p)^(n-k) and the geometry generated by its inverse-integer level sets. The binary level 2^(-n)

arXiv:2609.03590v1 Announce Type: cross Abstract: Timely delivery of delay-sensitive information over dynamic, heterogeneous networks is essential for NextG interactive applications, yet providing str

arXiv:2609.03350v1 Announce Type: cross Abstract: Pretraining data for Armenian, a morphologically rich and low-resource language, is scarce, and no open Armenian LLM has been released with the data a

arXiv:2609.03177v1 Announce Type: new Abstract: Frontier large language models (LLMs) have become attractive priors for optimization due to their large-scale pretraining that enables them to navigate

NVIDIA Jetson can run compact open‑source reasoning models such as Nemotron 3.5 Lightning (a mixture‑of‑experts architecture with 30 B total parameters but only ~3 B active per token) and dense Qwen 3

arXiv:2609.03889v1 Announce Type: cross Abstract: Contact-rich loco-manipulation requires a bridge between semantic action generation and physical interaction control. Existing Vision-language-action

arXiv:2609.03868v1 Announce Type: cross Abstract: Target-centered gaze interaction requires more than suppressing frame-to-frame fluctuations: target acquisition produces task-aligned changes in gaze-

Gemini 3.8 Flash might be maxxed on other benchmarks, but not quite on document parsing. We benchmarked it on ParseBench. It does slightly better on tables + content faithfulness compared to Gemini 3.

arXiv:2609.03193v1 Announce Type: cross Abstract: Nested sampling (NS) resolves the thermodynamics of an atomistic system from a single simulation, but its practical reach is limited by the Markov-cha

arXiv:2609.03724v1 Announce Type: cross Abstract: Bayesian Network (BN) fusion combines multiple input networks into a single structure, balancing dependency preservation with computational tractabili

arXiv:2609.03306v1 Announce Type: new Abstract: Kernelized graph methods - spectral clustering, diffusion maps, and sparse kernel -regression graphs - that use Gaussian kernels depend on the choice of

arXiv:2606.12821v2 Announce Type: replace Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis. New AI agents can be a helpful tool, but no benchmark