Search: “deployment”

Adversarial dynamical systems characterize when data-driven learning succeeds or fails

arXiv:2407.06312v2 Announce Type: replace-cross Abstract: Many systems resist analytical modeling, making data-driven inference of dynamics important. Yet data-driven methods can fail to converge or g

researcharxiv-cs-lg

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Agents

Agon: An Autonomous Large-Scale Omnidisciplinary Research System Built on Prompt Economy

DGX agent

arXiv:2606.24177v1 Announce Type: cross Abstract: Large language models are making research production scalable, shifting the bottleneck from producing artifacts to judging claims. We present extsc{Ag

agentsarxiv-cs-ai

24 Jun 2026

ATRIA: Adaptive Traceable ECG Reporting with Iterative Agents

arXiv:2606.24392v1 Announce Type: new Abstract: Existing ECG report generation is tightly coupled -- interpretation and reporting fused end-to-end, so errors propagate without stage-level recourse --

agentsarxiv-cs-ai

Best Preprocessing Techniques for Sentiment Analysis

arXiv:2606.24055v1 Announce Type: new Abstract: Sentiment analysis in Twitter datasets is important because it enables monitoring public opinion on products and analysis of political and social moveme

applicationsarxiv-cs-cl

Beyond the $7.8B in deals: Why Wall Street is suddenly watching Argentum AI

Is Argentum AI building the financing layer for the AI infrastructure boom? Yesterday, Barron’s reported that Argentum AI, the infrastructure startup led by Andrew Sobko and backed by Supermicro, had

hardwaresiliconangle

Beyond U-Net: A Latent-Representation-Aligned Skip-Free Backbone for Flow-Matching Speech Enhancement

arXiv:2606.24745v1 Announce Type: cross Abstract: Generative models, particularly diffusion and score-based approaches, have recently achieved strong performance in speech enhancement, but their itera

CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference

arXiv:2606.24467v1 Announce Type: new Abstract: Long-context large language model (LLM) inference is increasingly constrained by the memory footprint and decoding cost of key-value (KV) caches, limiti

Cryptographic certificates of validity for trustworthy AI

arXiv:2606.23768v1 Announce Type: cross Abstract: We propose cryptographic certificates of validity for agentic AI systems. The core idea is to formally specify a correctness or policy condition as a

Cycle-Consistent Neural Explanation of Formal Verification Certificates

arXiv:2606.24414v1 Announce Type: new Abstract: Formal verification produces machine-checkable certificates that attest to the satisfaction or violation of temporal properties, yet these certificates

Data Scale, Not Latency, Shapes Cross-Lingual Encoder Transfer in Streaming ASR

arXiv:2606.24169v1 Announce Type: new Abstract: Adapting a streaming speech recognition model to a new language requires choosing between two plausible warm starts: a multilingual (ML) encoder or an E

Decentralized Pose Graph Riemannian Optimization for Object-based Multi-Robot SLAM

arXiv:2606.24489v1 Announce Type: new Abstract: Pose graph optimization (PGO) is a key back-end component for state estimation in networked multi-robot simultaneous localization and mapping (SLAM). In

applicationsarxiv-cs-ro

Decentralized SGD with Controlled Disagreement Finds Flatter Minima

arXiv:2602.02899v2 Announce Type: replace Abstract: Decentralized training is often regarded as inferior to centralized training because the consensus errors between workers are thought to undermine c

safetyarxiv-cs-lg

Differential Unfolding: Efficient Unfolding Reconstruction for Video Snapshot Compressive Imaging

model-releasesarxiv-cs-cv

arXiv:2606.24153v1 Announce Type: new Abstract: While Deep Unfolding Networks (DUNs) dominate video Snapshot Compressive Imaging (SCI), they remain constrained by a uniform design philosophy. Existing

Does it matter which Gaussians you pick in 4D Gaussian streaming?

model-releasesarxiv-cs-cv

arXiv:2603.17227v3 Announce Type: replace Abstract: Anchor-driven 4D Gaussian streaming methods such as Instant Gaussian Stream (IGS) update a dynamic scene each frame from a compact set of Gaussian a

Evaluating LLM Usage for Efficient and Explainable Numerical and Classified Implicit Sentiment Analysis of Product Desirability

arXiv:2606.23701v1 Announce Type: cross Abstract: Qualitative product feedback can reveal nuanced user experiences, but its implicit sentiment is difficult to measure. This paper presents a scalable a

Event-Grounded Question Answering over Long Audio via Structured Retrieval

arXiv:2602.14612v4 Announce Type: replace-cross Abstract: Answering natural-language questions over multi-hour audio requires both event recognition and temporal grounding. Current large audio-languag

local-aiarxiv-cs-ai

Explaining Failures of Cyber-Physical Systems with Actual Causality

arXiv:2606.24546v1 Announce Type: new Abstract: Modern autonomous Cyber-Physical Systems (CPSs), such as self-driving cars, face increasingly complex demands, and yet are expected to act reliably. The

agentsarxiv-cs-ro

Female-RHINO: A Real-Time Scanner-Integrated Framework for Automated Quantitative Uterine MRI Analysis and Structured Reporting

arXiv:2606.24390v1 Announce Type: cross Abstract: Standardized assessment of uterine MRI remains challenging due to anatomical variability, observer dependence, and the lack of workflow-integrated aut

From 'Aha Moments' to Controllable Thinking: Toward Meta-Cognitive Reasoning in Large Reasoning Models via Decoupled Reasoning and Control

arXiv:2508.04460v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) can exhibit step-by-step reasoning, reflection, and backtracking, but these behaviors are often unregulated, leading t

Tools

GLM 5.2 Fast via Wafer now available on AI Gateway

GLM 5.2 Fast, a faster variant of the GLM language model, is now available through Wafer on Vercel's AI Gateway. This integration allows developers to access the optimized model through Vercel's platf

toolsvercel-blog

Hardware-Oriented Inference Complexity of Kolmogorov-Arnold Networks

arXiv:2604.03345v2 Announce Type: replace Abstract: Kolmogorov-Arnold Networks (KANs) have recently emerged as a powerful architecture for various machine learning applications. However, their unique

hardwarearxiv-cs-lg

Heterogeneous 2D/1D Signal Representation Fusion for Underwater Acoustic Modulation Recognition Under Distribution Shift

arXiv:2606.23702v1 Announce Type: cross Abstract: Modulation recognition systems rely on heterogeneous signal representations. 2D signal-image modalities such as time-frequency and cyclostationary map

How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation

model-releasesarxiv-cs-cl

arXiv:2606.16821v2 Announce Type: replace Abstract: Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that

Introducing the FFASR Leaderboard: Benchmarking ASR in the Real World

The FFASR Leaderboard is a benchmarking platform introduced by Hugging Face for evaluating Automatic Speech Recognition (ASR) systems on real-world performance metrics. It provides a standardized eval

applicationshugging-face

IPO Finance Agent: Evaluation of LLM Financial Analysts beyond Finance Agent v2, with Automated Rubric Generation -- the Case of the SpaceX (SPCX) IPO

arXiv:2606.23032v2 Announce Type: replace Abstract: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language model

JEDEL: Zero-Shot DNA-Encoded Library Design for Early-Stage Drug Discovery

arXiv:2606.23745v1 Announce Type: cross Abstract: We present JEDEL, a framework for generating synthesis-ready DNA-encoded libraries (DELs) directly from three-dimensional pharmacophore representation

LLMs Prompted for Legal Context Object More: Overrefusal from Small On-Premises LLMs in Criminal Legal Context

arXiv:2606.24585v1 Announce Type: new Abstract: While the validity of LLMs' use in the legal context remains subject to ethical and legal debate, legal professionals are already experimenting with per

local-aiarxiv-cs-ai

Machine Learning Modeling for Real-Time Melt Pool Monitoring in Laser Powder Bed Fusion Additive Manufacturing: A Hybrid Approach

model-releasesarxiv-cs-cv

arXiv:2606.23851v1 Announce Type: cross Abstract: This work investigates the implementation of artificial intelligence and machine learning (AI/ML) for real-time monitoring in laser powder bed fusion

Macro Graph of Experts for Billion-Scale Multi-Task Recommendation

model-releasesarxiv-cs-lg

arXiv:2506.10520v5 Announce Type: replace-cross Abstract: Graph-based multi-task learning at billion-scale presents a significant challenge, as different tasks correspond to distinct billion-scale gra

Industry

Microsoft's Digital Crimes Unit says AI helped it link two separate hacking tools, Amadey and StealC, and file a single civil lawsuit to help take them down (Lorelei Smillie/Bloomberg)

Lorelei Smillie / Bloomberg: Microsoft's Digital Crimes Unit says AI helped it link two separate hacking tools, Amadey and StealC, and file a single civil lawsuit to help take them down — Investigator

industrytechmeme

Military branches restore flu shot requirement after virus swept through base

After Secretary of Defense Pete Hegseth ended the military's flu shot mandate in April 2026, a major flu outbreak struck Lackland Air Force Base in Texas , with at least 222 recruits diagnosed with th

safetyars-technica

NVIDIA and AWS Collaborate to Bring AI to Production at Scale

Building AI systems at scale is demanding, requiring low-latency inference, fast vector search, strong GPU price-performance and infrastructure that can grow without multiplying operational complexity

hardwarenvidia-blog

One Year Later...The Harms Persist, But So Do We!

arXiv:2606.23884v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) are increasingly used for mental health-related conversations, yet safety safeguards remain inadequate an

OpenAI and Broadcom announce chip designed for LLM inference at scale

OpenAI and Broadcom unveiled Jalapeño, OpenAI's first Intelligence Processor designed specifically for LLM inference , with early testing showing substantially better performance per watt than current

hardwarears-technica

PORTER: Language-Grounded Event Representations for Portable Structured EHR Foundation Models

arXiv:2606.24102v1 Announce Type: new Abstract: Most electronic health record (EHR) foundation models encode clinical events as discrete event tokens from a fixed vocabulary and therefore cannot direc

researcharxiv-cs-cl

Probing the Misaligned Thinking Process of Language Models

arXiv:2606.24251v1 Announce Type: new Abstract: Large language models exhibit a growing range of misaligned behaviors such as strategic deception, sandbagging, and self-preservation. As they are incre

Progressive Pixel-Neighborhood Deformable Cross-Attention for Multispectral Object Detection

arXiv:2606.24092v1 Announce Type: new Abstract: Effective cross-modal feature alignment and interaction are central challenges in multispectral object detection. Although global cross-attention provid

local-aiarxiv-cs-cv

RIFT-Bench: Dynamic Red-teaming For Agentic AI Systems

arXiv:2606.23927v1 Announce Type: new Abstract: Agentic AI systems powered by large language models (LLMs) are rapidly evolving into autonomous decision-making systems, exposing attack vectors beyond

agentsarxiv-cs-ai

ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling

arXiv:2606.24605v1 Announce Type: new Abstract: Accurate user modeling often depends on rich interaction histories, which are unavailable for billions of low-activity users. Large Language Models (LLM

SlipSense: Multimodal Sensing for Online Slip Detection in Legged Robots

arXiv:2606.24350v1 Announce Type: new Abstract: Legged robots rely on accurate ground interaction awareness to traverse variable terrains, such as slippery surfaces. Existing slip detection methods of

researcharxiv-cs-ro

Sol Video Inference Engine: Agent-Native Full-Stack Acceleration Framework for Efficient Video Generation

arXiv:2606.23743v1 Announce Type: cross Abstract: Modern video diffusion models achieve higher generation quality through scaling, but this also increases inference cost. Although many acceleration me

agentsarxiv-cs-ai

The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs

arXiv:2504.17768v3 Announce Type: replace Abstract: Sparse attention offers a promising strategy to extend long-context capabilities in Transformer LLMs, yet its efficiency-accuracy trade-offs remain

applicationsarxiv-cs-cl

The vibe is shifting. Decentralized intelligence is making a comeback.

Clem Delangue discusses a resurgence of interest in decentralized intelligence systems and approaches, suggesting a shift away from centralized AI models toward more distributed architectures. The pos

local-aiclem-delangue--x

Thinking While Speaking: Inference-Time Knowledge Transfer for Responsive and Intelligent Conversational Voice Agents

arXiv:2511.07397v2 Announce Type: replace Abstract: Voice agents face a fundamental tension: the reasoning, retrieval, and tool use that make foundation models capable are iterative and slow, while co

agentsarxiv-cs-cl

Tuning without Peeking: Provable Generalization Bounds and Robust LLM Post-Training

arXiv:2507.01752v4 Announce Type: replace-cross Abstract: Gradient-based optimization is the workhorse of deep learning, offering efficient and scalable training via backpropagation. However, exposing

TurboMPC: Fast, Scalable, and Differentiable Model Predictive Control on the GPU

arXiv:2606.24039v1 Announce Type: new Abstract: Robotics increasingly relies on GPUs for parallel simulation, large-scale learning, and neural-network inference. For model predictive control (MPC) to

hardwarearxiv-cs-ro

What is actually limiting model routers for coding tasks? Most routers treat picking a model as a static, one-off classification. This paper…

What is actually limiting model routers for coding tasks? Most routers treat picking a model as a static, one-off classification. This paper identifies the real bottleneck as information deficit. Simp

agentsdair-ai--x

World Models in Pieces: Structural Certification for General Agents

arXiv:2606.24842v1 Announce Type: new Abstract: In the big-world regime, agents cannot be universally capable and their ability is inevitably specialized across a world model in pieces. Consequently,

local-aiarxiv-cs-ai