Search: “models”

arXiv:2607.19954v1 Announce Type: new Abstract: Detecting media bias automatically is difficult because biased framing is often subtle, yet in domains such as news analysis, accurate predictions alone

arXiv:2607.19191v1 Announce Type: new Abstract: We present ABot-World-0, an action-conditioned video world model for real-time, long-horizon closed-loop interaction, supported by a multi-source data i

arXiv:2607.19855v1 Announce Type: new Abstract: Adversarial robustness is commonly evaluated with predefined attack ensembles, such as AutoAttack, at a single perturbation budget arepsilon and on a se

arXiv:2607.19742v1 Announce Type: cross Abstract: Cyber Threat Intelligence (CTI) reports richly describe real-world attack processes, but their unstructured narratives cannot be directly used for aut

arXiv:2607.19771v1 Announce Type: cross Abstract: Muon and related matrix-sign optimizers are increasingly used to pre-train large language models, but their effect on the internal geometry of individ

arXiv:2607.18539v1 Announce Type: new Abstract: Novel view rendering of large and complex reconstructed scenes is becoming increasingly photorealistic. However, most reconstructions remain static and

arXiv:2607.19344v1 Announce Type: new Abstract: Controllable image generation remains challenging for creative professionals, who often require precise regional control over materials, object identiti

arXiv:2601.06487v3 Announce Type: replace-cross Abstract: Reinforcement learning has substantially improved the performance of LLM agents on tasks with verifiable outcomes, but it still struggles on o

arXiv:2607.20124v1 Announce Type: new Abstract: Tsetlin Machine (TM) is a rule-based machine-learning algorithm comprising collectives of two-action Tsetlin Automata (TAs) that cooperatively form conj

arXiv:2607.18997v1 Announce Type: new Abstract: Information Extraction (IE) from Architecture, Engineering, and Construction (AEC) drawings remains hindered by manual inefficiency, while Layout Detect

arXiv:2607.19843v1 Announce Type: cross Abstract: Large language models (LLMs) have made automated program repair (APR) increasingly practical for real-world bugs, but repairing directly from bug repo

arXiv:2607.19515v1 Announce Type: cross Abstract: Continuous surveillance video creates a growing storage, transmission, and inference burden for enterprise video analytics systems. While modern codec

arXiv:2607.19519v1 Announce Type: cross Abstract: Most 3D properties relevant to molecular design, including free energies and shape descriptors, are extit{expectations} over the Boltzmann distributio

arXiv:2607.19386v1 Announce Type: cross Abstract: Cross-paper comparison of sparse autoencoder (SAE) interpretability often relies on autointerpretability scores. In this evaluation pipeline, a langua

In this post, we explore how Jefferies overcame these challenges with a solution built on Strands Agents, an agent harness SDK for building AI agents that can reason, plan, and act by orchestrating ca

arXiv:2607.18678v1 Announce Type: new Abstract: Breast MRI is highly sensitive for detecting breast tumors, but exams contain many slices and require substantial reading time. Deep learning models oft

arXiv:2607.18700v1 Announce Type: new Abstract: The FathomNetCLEF 2026 competition combines underwater object detection and fine-grained marine species classification under a positive-unlabeled evalua

arXiv:2407.08233v3 Announce Type: replace Abstract: Current differentially private learning paradigms face a severe utility bottleneck: DP-SGD degrades performance through noise accumulation over trai

arXiv:2409.19279v2 Announce Type: replace-cross Abstract: Continuous-time models can reveal accelerated structures in distributed optimization, but their rates need not survive direct discretization.

arXiv:2607.19704v1 Announce Type: new Abstract: Scaling LLM-based applications to millions of users is bottlenecked by the inference cost and latency of modern foundation models. A natural fix is to c

arXiv:2607.19617v1 Announce Type: new Abstract: As autonomous systems and smart cities continue to evolve, the demand for efficient and robust scene understanding becomes increasingly critical. Semant

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