Search: “applications”

Asymptotic Risk Calibration for Selective Question Answering

arXiv:2608.12008v1 Announce Type: new Abstract: Large language models (LLMs) may generate fluent but incorrect answers, making uncertainty quantification important for reliable question answering. How

researcharxiv-cs-cl

Benchmarking Trustworthiness of SLMs: Pre-trained vs. Compressed

DGX agent

arXiv:2608.11981v1 Announce Type: new Abstract: Small Language Models (SLMs) have emerged as a more efficient alternative to traditional Large Language Models (LLMs), offering promising potential in r

safetyarxiv-cs-cl

13 Aug 2026

BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents

arXiv:2511.20597v2 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) agents into web browsers introduces security challenges that go beyond traditional web applica

Can Frontier LLMs Match Natively Multimodal Embeddings? A Comparison on Hard-Negative Text-to-Image Retrieval

arXiv:2608.11343v1 Announce Type: new Abstract: Multimodal retrieval and classification across different types of media, spanning text, images,video and audio, has traditionally relied on dual-encoder

Constructing Dynamic Master Logic Models as Knowledge Graphs for Complex System Diagnostics Using Retrieval-Augmented Large Language Models

arXiv:2608.12304v1 Announce Type: new Abstract: Dynamic Master Logic (DML) provides a hierarchical framework for representing system behavior by linking functional objectives to underlying structural

CookVoice: Unified Framework for Style Controllable Multi-Modal Human Voice Generation

arXiv:2608.11590v1 Announce Type: cross Abstract: Human voice generation has made rapid progress in speech generation, singing voice generation, voice cloning, and voice editing. However, most existin

safetyarxiv-cs-lg

Cross-Corpus Evaluation of Generalizable Vulnerability Detection in IoT Firmware

model-releasesarxiv-cs-lg

arXiv:2608.11492v1 Announce Type: cross Abstract: IoT firmware vulnerability detection remains challenging due to heterogeneous firmware ecosystems, resource-constrained platforms, and limitations in

Deep Learning Based Relative Transfer Matrix Estimation for Multiple Sources and Multiple Microphones

arXiv:2608.11627v1 Announce Type: cross Abstract: The Relative Transfer Matrix (ReTM), recently introduced as a generalization of the relative transfer function for multiple receivers and sources, sho

researcharxiv-cs-ai

Diffusion Probe: Generated Image Result Prediction Using CNN Probes

arXiv:2602.23783v5 Announce Type: replace Abstract: Text-to-image (T2I) diffusion models lack an efficient mechanism for early quality assessment, leading to costly trial-and-error in multi-generation

agentsarxiv-cs-cv

Distribird: Literature-Informed Prior Distribution Design for Bayesian Model Calibration

arXiv:2608.11210v1 Announce Type: new Abstract: Bayesian calibration of process-based models requires a prior distribution for each model parameter. Despite decades of methodological work, researchers

Dual Anchors, Do It Better: Hierarchical Group Merging for Zero-Shot Anomaly Detection

arXiv:2608.11933v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) aims to identify anomalies in unseen domains, a setting that is particularly critical for industrial and medical appl

safetyarxiv-cs-cv

Heterogeneous transfer learning for high-dimensional regression with feature mismatch

arXiv:2412.18081v3 Announce Type: replace-cross Abstract: We study Heterogeneous Transfer Learning (HTL) for high-dimensional regression with differing feature sets. Such feature mismatch arises when

Inverse Theory of Mind Modeling for Content Recommendation: From Web Browsing to Dynamic Intelligent Interfaces

arXiv:2608.11354v1 Announce Type: new Abstract: Modern recommender systems treat observed actions as reliable proxies for user preferences, yet interactions often reflect exploration or comparison rat

Large Language Models Reproduce Racial Stereotypes When Used for Text Annotation

arXiv:2603.13891v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for automated text annotation in tasks ranging from academic research to content moderation

LiveAnimate: Stable Long-Form Streaming Human Animation in Real-Time

model-releasesarxiv-cs-cv

arXiv:2608.11745v1 Announce Type: new Abstract: Pose-driven human animation synthesizes a video of a target person from a single reference image and a driving pose stream. Real-time generation is esse

MicroAUNet: Boundary-Enhanced Multi-scale Fusion with Knowledge Distillation for Colonoscopy Polyp Image Segmentation

arXiv:2511.01143v2 Announce Type: replace-cross Abstract: Early and accurate segmentation of colorectal polyps is critical for reducing colorectal cancer mortality, which has been extensively explored

New Orthogonal Multiwavelet Filters Derived by Matrix Spectral Factorization

arXiv:2608.11518v1 Announce Type: new Abstract: The paper considers the construction of two new orthogonal multiwavelets with supercompact support by using the Fast Bauer's method for matrix spectral

researcharxiv-cs-cv

No One to Blame: A Framework of Constitutive AI Unaccountability

arXiv:2608.12104v1 Announce Type: cross Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms. Existing research predominantly frames A

agentsarxiv-cs-ai

ODE-Based Transformer Decoders for Iterative Sign Language Translation

model-releasesarxiv-cs-cl

arXiv:2608.11352v1 Announce Type: new Abstract: Sign language translation has achieved strong results with Transformer architectures, yet recent improvements largely rely on scaling model capacity at

On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations

arXiv:2604.03086v2 Announce Type: replace-cross Abstract: This work establishes a rigorous bridge between infinite-dimensional delay dynamics and finite-dimensional Koopman learning, with explicit and

OpenAg: Democratizing Agricultural Intelligence

arXiv:2506.04571v3 Announce Type: replace Abstract: Agriculture is undergoing a major transformation driven by artificial intelligence (AI), machine learning, and knowledge representation technologies

agentsarxiv-cs-ai

ScreenShot: A Foundation Model for Few-Shot Combination Drug Screening

arXiv:2608.12219v1 Announce Type: new Abstract: Treating patients with combinations of drugs reduces the risk of resistance to any individual drug. Finding effective combinations is difficult because

Self-Harness: Harnesses That Improve Themselves

model-releasesarxiv-cs-cl

arXiv:2606.09498v2 Announce Type: replace Abstract: The performance of LLM-based agents is jointly shaped by their base models and the harnesses that mediate their interaction with the environment. Be

Test-Time Hallucination Control in Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2608.11474v1 Announce Type: new Abstract: Object Hallucination in large vision-language models (LVLMs), where models generate non-factual content about input images, remains a critical barrier t

The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark

arXiv:2608.11469v1 Announce Type: cross Abstract: AI agents are rapidly improving in cybersecurity capabilities when the source code is available for analysis, yet much of the software most consequent

The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy

arXiv:2607.11175v2 Announce Type: replace Abstract: The growing ability of large language models and vision-language models to jointly interpret and reason over images and text is reshaping medical im

Vision-Reasoning-Guided Occlusion Removal from Light Fields

model-releasesarxiv-cs-cv

arXiv:2606.19985v2 Announce Type: replace Abstract: Occlusion-robust scene recovery remains a major challenge in computational imaging, particularly where dense vegetation severely limits visibility.

Agentic AI infrastructure shifts enterprise focus from model choice to platform control

As agentic AI infrastructure moves from experimentation into production, enterprises are confronting a more complex question than which model to use: how to control the cost, data exposure and infrast

agentssiliconangle

Agentic Instruction Data Selection: Let DataMaster Interpret Your Intent

arXiv:2608.10579v1 Announce Type: new Abstract: Although existing instruction data selection methods have introduced various metrics, the inherent complexity of real-world datasets makes it impractica

agentsarxiv-cs-ai

Attention-Path Fragility as an Uncertainty Signal in Large Language Models

arXiv:2608.11138v1 Announce Type: cross Abstract: We propose that a model's uncertainty about a token is reflected not only in the breadth of its output distribution but also in whether a confident pr

Calibrating Post-Training Feature Shifts for LLM Data Contamination Detection

arXiv:2608.10462v1 Announce Type: new Abstract: Large language models (LLMs) are trained on massive and largely undisclosed corpora that may contain copyrighted or privacy-sensitive content. Data cont

researcharxiv-cs-cl

Capturing Uncertainty in Human Motion for Representation Learning in Soccer

arXiv:2608.11203v1 Announce Type: new Abstract: This paper presents a self-supervised representation learning framework for understanding 3D skeleton-based human motion in soccer, using future motion

researcharxiv-cs-cv

CHORUS: Complementary Experts for High-Coverage Testbench Stimulus Generation

arXiv:2608.10090v1 Announce Type: new Abstract: Large language models (LLMs) have advanced code generation, where executable feedback provides a more reliable learning signal than textual imitation al

ChronoSSM: Training for Temporally Aware Representations in Autoregressive State Space Models

arXiv:2608.10120v1 Announce Type: new Abstract: Modern sequence models, from Transformers to State Space Models, have enabled powerful generative modeling across diverse domains, yet they are typicall

CohereLabs/North-Micro-Vision-Instruct · Hugging Face

model-releasesr-localllama

North Micro Vision Instruct is a 2.4B-parameter open-weight vision-language model with native-resolution image support, released under the Apache 2.0 license. It is designed as a compact foundation fo

Dynamic Context Adapters: Efficiently Infusing History into Vision-and-Language Models

arXiv:2608.10525v1 Announce Type: cross Abstract: Historical context integration presents a fundamental challenge for Vision-Language Models (VLMs) in sequential decision-making tasks. Current VLMs pr

researcharxiv-cs-ai

Edge Phoneme Recognition for Children's Speech through Age-Aware Training

arXiv:2608.10206v1 Announce Type: new Abstract: Detecting phonemes from children's speech has historically been difficult due to the scarcity of training data, and unique characteristics of children's

Efficient Weak-Entropy PINN for Solving Hyperbolic Conservation Laws

arXiv:2608.10389v1 Announce Type: cross Abstract: In recent years, neural networks have significantly advanced numerical solutions of partial differential equations (PDEs). However, solving PDEs with

Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608.09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis. Deep learning (DL) mod

researcharxiv-cs-ai

Generalized Linear Markov Decision Process

arXiv:2506.00818v2 Announce Type: replace-cross Abstract: Offline reinforcement learning for longitudinal studies often faces two linked challenges: rewards may be binary or bounded, and reward observ

Hardware

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads wit

hardwarearxiv-cs-ai

I believe the demand for compute is going to go up faster than the supply of compute, so the price of compute is going to increase significa…

I believe the demand for compute is going to go up faster than the supply of compute, so the price of compute is going to increase significantly in the future, perhaps as much as 10x in the next few y

agentssonya-huang--x

INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators

arXiv:2608.10492v1 Announce Type: new Abstract: Large Language Model (LLM)-based simulators often reproduce observable actions but fail to capture the underlying reasoning behind them. In education, w

Local Ai

LiquidAI/LFM2.5-VL-3B · Hugging Face

LFM2.5-VL-3B is a multimodal variant of LFM2.5, a family of hybrid models designed for on-device deployment. It builds on LFM2-VL-3B with further mid- and post-training. LFM2.5-VL-3B can process both

local-air-localllama

Physics-Informed Machine Learning in Prognostics and Health Management: A Systematic Literature Review

arXiv:2608.10047v1 Announce Type: cross Abstract: In modern industry, keeping complex systems reliable, safe, and efficient hinges on Prognostics and Health Management (PHM). Machine Learning (ML) has

PolypVision: A Three-Stage Hierarchical Deep Learning Framework for Classification and Segmentation of Colorectal Polyps

arXiv:2608.10649v1 Announce Type: new Abstract: Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide, predominantly arising from precancerous polyps. Accurat

researcharxiv-cs-cv

Local Ai

Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory

arXiv:2608.11066v1 Announce Type: cross Abstract: We prove inference-time quantum coordination advantages for specified AI state-tracking tasks. A solver compresses semantic history into a future-acce

local-aiarxiv-cs-ai

Qwen3.8-2.4T-A95B is now live on Together AI. The Qwen Team’s latest flagship model is built for coding and long-horizon agent workflows, wi…

model-releasestogether-ai--x

The Qwen Team has released its flagship model, Qwen3.8‑2.4T‑A95B, on the Together AI platform (togethercompute) as of August 12 2026. This 2.4‑trillion‑parameter model is engineered for coding tasks a