Search: “tools”

ACM: Agentic Context Management for Long Horizon Tasks

arXiv:2607.23809v1 Announce Type: new Abstract: Agentic tasks are inherently long-horizon and multi-turn, constantly accumulating context through interactions with the environment. Existing context co

agentsarxiv-cs-ai

Act, Think or Abstain: Complexity-Aware Adaptive Inference for Vision-Language-Action Models

DGX agent

arXiv:2603.05147v2 Announce Type: replace Abstract: Current research on Vision-Language-Action (VLA) models predominantly focuses on enhancing generalization through reasoning techniques. While effect

researcharxiv-cs-cv

28 Jul 2026

Agentic Permissions Policy Algebra for Taint Confinement in LLM Agents

arXiv:2607.24625v1 Announce Type: cross Abstract: Autonomous LLM agents processing mixed-confidentiality data face severe security risks from prompt injection attacks and reasoning errors. While dynam

Agentic Reward Modeling: Verifying GUI Agent via Progressive Trajectory-Grounded Interaction

arXiv:2602.00575v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a promising pathway for continuously advancing GUI agents, yet existing reward modeli

agentsarxiv-cs-ro

AI Strategy: How to Choose What AI Product to Implement

arXiv:2607.23733v1 Announce Type: cross Abstract: Firms struggle to choose AI projects that pay off: two projects can look equally promising to smart, motivated stakeholders and yet deserve opposite d

tutorialsarxiv-cs-ai

An adaptive multi-fuzzy logic model for diagnosing transformer faults using dynamic weight optimization

arXiv:2607.23486v1 Announce Type: new Abstract: Dissolved gas analysis (DGA) is crucial for diagnosing early power transformer failures. Traditional DGA interpretation methods like Duval Triangle, IEC

researcharxiv-cs-lg

An Unofficial FastLAS Tutorial: A Programmer's Guide

arXiv:2607.23557v1 Announce Type: cross Abstract: FastLAS is a scalable system for Inductive Logic Programming (ILP): you give it some background knowledge, a language bias, and a set of examples, and

ARdena: Scenario-driven control of real-time LLM agents

arXiv:2607.22651v1 Announce Type: new Abstract: Large language models (LLMs) have enabled increasingly capable conversational agents, but reliably controlling their behavior in real-time interactive e

At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone. We believe that, at some point in th…

At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone. We believe that, at some point in the future, AI acceleration for frontier model development may

tutorialsopenai--x

Beyond Shapley: An Influence-Based Data Auditing Pipeline for LLM Alignment and Evaluation

arXiv:2607.22766v1 Announce Type: cross Abstract: The alignment of Large Language Models (LLMs) is increasingly bottlenecked by data quality. As datasets scale, massive preference and instruction-tuni

CausAdv: A Causal-based Framework for Detecting Adversarial Examples

arXiv:2411.00839v4 Announce Type: replace-cross Abstract: Deep learning has led to tremendous success in computer vision, largely due to Convolutional Neural Networks (CNNs). However, CNNs have been s

Co-Harness: Co-Evolving Harnesses and Model Weights for LLM Agents

arXiv:2607.22688v1 Announce Type: new Abstract: Post-training agents for automated AI research requires optimizing not only model parameters, but also the runtime harness that shapes how research traj

local-aiarxiv-cs-ai

Coding agents are helping scientists spend more time advancing research, taking on everything from routine maintenance and targeted optimiza…

Coding agents are helping scientists spend more time advancing research, taking on everything from routine maintenance and targeted optimization to complete redesigns and new systems. While agents can

model-releasesopenai--x

Concept-based Visual Counterfactual Explanations with Diffusion Models

arXiv:2607.22544v1 Announce Type: new Abstract: Visual counterfactual explanations aim to answer 'what minimal change to this image would flip the model's prediction?', and are increasingly important

Continual-RL for Generalization in Autonomous Racing on the RoboRacer Platform

arXiv:2607.24320v1 Announce Type: new Abstract: A key challenge in modern robotics is to adapt to changing environments, a challenge that is exacerbated when simulations cannot encompass every possibl

safetyarxiv-cs-ro

Continuous surrogates versus threshold Boolean networks for modeling Arabidopsis ISR gene regulation

arXiv:2607.23289v1 Announce Type: cross Abstract: Gene regulatory network modeling often requires balancing predictive accuracy and mechanistic interpretability. In this work, we compare continuous su

researcharxiv-cs-lg

DataOrchestra: Learning to Orchestrate Per-Example Curation of Pretraining Data

arXiv:2607.24717v1 Announce Type: cross Abstract: Pretraining data processing is critical to the downstream performance of Large Language Models (LLMs). However, many existing approaches define a fixe

Directional Influence Function: Estimating Training Data Influence in Constrained Learning

arXiv:2607.23388v1 Announce Type: cross Abstract: As constrained learning becomes increasingly common, models are trained under explicit feasibility requirements to enforce fairness, safety, robustnes

DispatchRAG: Grounding Emergency Dispatch Decisions in Real-World Protocols from Traffic Accident Video

arXiv:2607.23132v1 Announce Type: new Abstract: Assessing the severity of a traffic accident scenario is important to decide which emergency service to dispatch. Missing an ambulance dispatch on a ped

agentsarxiv-cs-cv

DocHRL: A Hierarchical Reinforcement Learning Framework for Cost-Optimised Document Classification

arXiv:2607.22644v1 Announce Type: new Abstract: Real-world document classification pipelines typically apply the same sequence of models to every incoming document, regardless of its complexity or typ

Evaluating LLMs as Interpretable Controllers for Dynamical Systems

arXiv:2607.22609v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for decision-making and reasoning tasks, yet their potential as controllers for physical systems rema

Extending Desbordante with Probabilistic Functional Dependency Discovery Support

arXiv:2607.23636v1 Announce Type: cross Abstract: Data profiling aims to extract complex patterns from data for further analysis and use that data in domains such as data cleaning, data deduplication,

tutorialsarxiv-cs-ai

False Prophets: On the Security of World Models in Agentic Systems

arXiv:2607.23147v1 Announce Type: cross Abstract: Large language models now power autonomous agents capable of complex, multi-step tasks in different environments. Accurate and reliable execution of t

From transcription to semantic corpus analysis: unsupervised learning of sentence representations for ancient languages

model-releasesarxiv-cs-cl

arXiv:2607.24542v1 Announce Type: new Abstract: Automatic Text Recognition (ATR) now supplies digital humanities with large volumes of unstructured, heterogeneous, and often noisy text in ancient lang

Grading the Narrators: An Isnad-Rijal Framework for Claim-Level Provenance in Multi-Agent Knowledge Systems

arXiv:2607.24117v1 Announce Type: new Abstract: Modern multi-agent knowledge systems increasingly accumulate knowledge through chains of autonomous transformations rather than direct retrieval. Existi

agentsarxiv-cs-ai

Applications

ID-V2V: Identity-Preserving Video Restylization

arXiv:2607.22830v1 Announce Type: new Abstract: In visual storytelling, human performances are central to creative intent and narrative meaning. However, preserving human identity and performance whil

applicationsarxiv-cs-cv

Invariant Discovery for Networked Systems

arXiv:2607.22944v1 Announce Type: cross Abstract: Invariants, the relations expected to hold among measured signals of a network, underpin applications from verification to traffic generation, telemet

tutorialsarxiv-cs-ai

LanteRn: Latent Visual Structured Reasoning

arXiv:2603.25629v2 Announce Type: replace Abstract: While language reasoning models excel in many tasks, visual reasoning remains challenging for current large multimodal models (LMMs). As a result, m

researcharxiv-cs-cv

Let AI Agents Translate Networks, Not Reason About Them

arXiv:2607.22947v1 Announce Type: new Abstract: A formal model enables verifying reachability, localizing an outage, or anticipating the blast radius of a change. Yet, virtually no production network

local-aiarxiv-cs-ai

LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

arXiv:2411.00918v5 Announce Type: replace-cross Abstract: Mixture of experts (MoE) architectures have become a cornerstone for scaling up and are a key component in most large language models such as

LLM-SoccerArena: Benchmarking LLMs on Real-World Predictions in Sports

arXiv:2607.24573v1 Announce Type: new Abstract: Large language models (LLMs) increasingly support decisions about uncertain future events, yet evaluating their ability to forecast real-world outcomes

Making Mathematical Knowledge Explainable, Accessible and Interoperable Through Large Language Model Integration

arXiv:2607.24512v1 Announce Type: new Abstract: Mathematical models are central to formalizing research problems, yet their documentation often falls short of FAIR principles. Knowledge bases such as

MANGO: A Global Single-Date Paired Dataset for Mangrove Segmentation

arXiv:2601.17039v2 Announce Type: replace-cross Abstract: Mangroves are critical for climate-change mitigation, requiring reliable monitoring for effective conservation. While deep learning has emerge

ML-based Predictive Models for Power Consumption in Virtualised O-RANs

arXiv:2607.24256v1 Announce Type: cross Abstract: As communication networks adopt virtualized and disaggregated architectures, achieving energy efficiency has become increasingly important for both ec

Mwando: Leveraging AI to Preserve and Teach shiKomori

arXiv:2607.23481v1 Announce Type: new Abstract: This paper presents Mwando, a virtual educational assistant designed to support the teaching and preservation of shiKomori, the language of the Comoros

agentsarxiv-cs-cl

Neptuna: A Comprehensive Machine Learning Framework for Benchmarking Complex Multiphase Flows

arXiv:2607.22280v2 Announce Type: replace-cross Abstract: Compressible multiphase flows involving shocks and material interfaces arise in applications such as bubble collapse and droplet breakup, wher

New research from Meta and CMU. This one is on agentic context management for long horizon tasks. (bookmark it) Production agents accumulate…

New research from Meta and CMU. This one is on agentic context management for long horizon tasks. (bookmark it) Production agents accumulate context every turn. The usual fix compresses on a token thr

model-releasesdair-ai--x

Now, this: 1,100 current/former frontier-AI employees sign a petition calling for US gov't to step in for 'pacing' frontier development

So, it appears that this is the week of open letters in AI🥲... an open letter signed by current and former employees of OpenAI, Anthropic and Google primarily - calling for a slow-down in frontier AI

local-air-localllama

Order in Desbordante: Techniques for Efficient Implementation of Order Dependency Discovery Algorithms

arXiv:2607.23632v1 Announce Type: cross Abstract: Science-intensive data profiling focuses on discovery and validation of various patterns in datasets. This study considers discovery of one such patte

ParasGB: A Graph Benchmark Suite for Parasitic Estimation on AMS Circuits

model-releasesarxiv-cs-lg

arXiv:2607.23225v1 Announce Type: new Abstract: As chip manufacturing processes advance to deep submicron nodes, parasitic interconnect effects increasingly dominate the performance of analog and mixe

Physics-Guided Generative AI for Property-Targeted 3D Porous Media Design

arXiv:2607.24274v1 Announce Type: cross Abstract: Inverse design of three-dimensional porous media is central to applications in filtration, catalysis, energy storage, fuel cells, thermal management,

PIRL: From Open-Loop Exploration to Closed-Loop Reinforcement Learning [R]

local-air-machinelearning

TL;DR: Most RL post-training algorithms optimize the current batch and move on. But after an update, did the new policy actually become better? We introduce Policy Improvement Reinforcement Learning (

Pointer-Augmented Autoregressive Generation of Patent Claims with Joint Topology and Content Decoding

model-releasesarxiv-cs-cl

arXiv:2607.24040v1 Announce Type: new Abstract: Autoregressive decoders emit flat token sequences and cannot enforce hierarchical constraints across output segments, a limitation that becomes acute in

Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)

arXiv:2607.18263v2 Announce Type: replace Abstract: AI-generated non-consensual intimate imagery (AIG-NCII) is not adequately addressed in AI/ML literature regarding AI-generated media, commonly refer

Reading Between the Signs: Predicting Future Suicidal Ideation from Adolescent Social Media Texts

arXiv:2509.03530v2 Announce Type: replace Abstract: Suicide is a leading cause of death, yet predicting it remains a significant challenge. Risk factors such as depression or substance use are commonl

researcharxiv-cs-cl

Retrieval-Augmented Large Language Models as Components of Cognitive Computing architecture for Regulatory Knowledge Management

arXiv:2607.24352v1 Announce Type: new Abstract: The aim of this article is to verify whether integrating large language models (LLMs) with the Retrieval-Augmented Generation (RAG) architecture enables

local-aiarxiv-cs-cl

Revitalizing Public Urban Places through Cultural and Political Memory: A Technological Approach with LLMs and Augmented Reality

arXiv:2607.22613v1 Announce Type: cross Abstract: This paper explores the intersection of memory, place, and identity, examining how new technologies, particularly Apple Vision Pro, can illuminate thi

SIREN: Towards End-to-End Extreme-Weather Early Warning with Experience-Grounded LLM Agents

arXiv:2607.24588v1 Announce Type: new Abstract: Early warning of extreme weather is essential for mitigating the societal, economic, and environmental risks posed by hazardous weather events. However,