Search: “tools”

A Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors

arXiv:2609.03884v1 Announce Type: cross Abstract: Modern AI agent harnesses expose lifecycle hooks that bind shell commands to runtime events such as session start, tool calls, and file edits. These c

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Agents

A Case Study on Emergent Cheating and Whistleblowing in Autonomous Research Swarms

DGX agent

arXiv:2609.04170v1 Announce Type: new Abstract: Multi-agent AI science ecosystems rely on agents possessing tools that allow them to communicate, coordinate, and build on each other's work. Yet this s

agentsarxiv-cs-ai

4 Sept 2026

A Multi-Vine Soft Robot Enabling Accessible Working Channel and Steering

arXiv:2609.03758v1 Announce Type: new Abstract: Soft eversion robots, also known as vine robots, have attracted growing interest for navigation and inspection tasks, including minimally invasive medic

researcharxiv-cs-ro

Counterfactual Fairness Audits of Multi-Step Clinical LLM Agents Require a Measured Per-Action Instability Floor

arXiv:2609.03221v1 Announce Type: new Abstract: Counterfactual audits are the standard tool for checking whether a clinical agent treats demographically distinct but clinically identical patients diff

Counting Animals in Camera-Traps Image Sequences without Count Labels: Winning Solution to the iWildCam 2021 Challenge

model-releasesarxiv-cs-cv

arXiv:2609.03233v1 Announce Type: new Abstract: Camera traps have become an essential tool for wildlife monitoring, motivating the development of computer vision methods for the automated extraction o

CROCODIL: Cross-Model Code Editing with LLMs

arXiv:2609.03894v1 Announce Type: new Abstract: Large language models (LLMs) have become ubiquitous tools for code generation and editing. However, development teams often use multiple LLM assistants.

safetyarxiv-cs-cl

DropClick: Semi-Automated One-Click Segmentation for Agricultural Robotic Data

arXiv:2609.03680v1 Announce Type: new Abstract: Labelling vision datasets, especially for segmentation tasks, is a laborious and costly process that stymies novel developments in agricultural robotics

researcharxiv-cs-cv

Equilibria for Networks of Linear Translational Springs

model-releasesarxiv-cs-ro

arXiv:2609.03143v1 Announce Type: cross Abstract: We use tools from nonlinear algebra to study the equilibria of small linear translational spring networks. Specifically we use the techniques of homot

FiMI Banking: A Sovereign Model for Indian Retail Banking

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

IDSPACE: A Novel Document Generator for Reliable Evaluation of Digital Identity Verification Systems [Extended Technical Report]

model-releasesarxiv-cs-cv

arXiv:2609.03052v1 Announce Type: new Abstract: As services move online, trust institutions such as banks, lenders, and governments must verify the identity of remote users. Fraud detection tools are

RL-ADA: A World-Feedback Framework for Adversarially Robust Enterprise Dialogue Agents

arXiv:2609.02902v1 Announce Type: new Abstract: Deploying task-oriented dialogue agents in enterprise customer support faces a persistent annotation bottleneck: robust training requires labelled inter

agentsarxiv-cs-cl

Sharpening the Ensemble: An SSIM-Aligned Residual Refiner for Brain-MRI Inpainting Post-Processing

model-releasesarxiv-cs-cv

arXiv:2609.03981v1 Announce Type: new Abstract: Brain-MRI inpainting replaces a masked region of a scan with synthesized, anatomically plausible healthy tissue, so that analysis tools built for health

Synthetic Semantic Supervision for Contrastive Code Representation Learning in Small Transformers: An Empirical Study

arXiv:2609.03702v1 Announce Type: new Abstract: General-purpose code embeddings power tools for code search, classification, and retrieval. Compact transformer encoders for code typically rely on eith

Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment

arXiv:2601.04736v2 Announce Type: replace Abstract: Despite remarkable capability in multi-modal understanding, deploying Multi-modal Large Language Models (MLLMs) in open-ended conversational scenari

safetyarxiv-cs-cl

A computational approach to maximum likelihood thresholds for colored Gaussian graphical models

arXiv:2609.02382v1 Announce Type: cross Abstract: Gaussian graphical models (GGMs) are essential tools for interpretable structure learning. However, in high-dimensional, small-sample regimes, the ava

researcharxiv-cs-lg

Applications

Addressing Trust in AI Systems through Education: A Didactic Perspective

arXiv:2609.02453v1 Announce Type: cross Abstract: Machine learning (ML) education faces two persistent and connected obstacles: many educational tools present ML as an opaque black box, which leaves l

applicationsarxiv-cs-ai

AI agents reshape consensus formation in human groups

arXiv:2609.02122v1 Announce Type: new Abstract: As large language model (LLM) agents shift from tools to participants in human groups, a fundamental question for collective behavior is how their growi

agentsarxiv-cs-cl

APEx: Distillation of Agent Procedural Experience for Adaptive Deep Research Question Answering

arXiv:2609.02253v1 Announce Type: new Abstract: Deep research agents augment large language models with external tools to answer complex, long-horizon questions through multi-turn reasoning. Learning

Local Ai

Automated Vulnerability Injection in Smart Contracts Using Large Language Models

arXiv:2609.02624v1 Announce Type: cross Abstract: Assessing vulnerability detection tools for smart contracts requires datasets with known ground truth, yet such datasets are scarce and difficult to b

local-aiarxiv-cs-ai

Contrastive Explanations in Quantitative Bipolar Argumentation Frameworks

arXiv:2609.02399v1 Announce Type: new Abstract: Argumentation frameworks are useful tools for representing and reasoning with information in a variety of settings, e.g. in supplementing AI models as t

safetyarxiv-cs-ai

Convergence Theory of Knowledge Distillation in Asynchronous P2P Gossip Learning Network

arXiv:2609.01952v1 Announce Type: cross Abstract: Decentralized, serverless learning increasingly connects devices running different architectures, where the standard tool, decentralized SGD, is undef

Learning to Fuse LLMs with Ontology Rankers for Rare-Disease Diagnosis

arXiv:2609.02473v1 Announce Type: new Abstract: Ontology rankers remain useful for rare-disease diagnosis because each candidate can be traced to matched patient phenotypes. Large language models (LLM

Ranked by the Matcher: A Reproducibility Audit of Knowledge Graph Extraction from Threat Reports

arXiv:2609.01671v1 Announce Type: cross Abstract: Security teams and researchers choose knowledge-graph extraction tooling for threat reports on the strength of published triple-F1 scores, yet those s

researcharxiv-cs-ai

AI Should Not Only Be Helpful. It Should Be Contingent. Artificial Intimacy, Sycophancy, and the Future of Social Learning

arXiv:2609.00211v1 Announce Type: new Abstract: Conversational artificial intelligence is increasingly embedded in everyday social environments, where it functions as both an informational tool and a

safetyarxiv-cs-ai

Autonomous discovery of new structure-plausibility laws for explainable and rapid crystal diagnosis and screening

arXiv:2609.01209v1 Announce Type: cross Abstract: Crystal generators and tool-using agents propose structures faster than density functional theory (DFT) energy and phonon calculations or experiments

Beyond Scores: Understanding LLM-as-a-Judge Mechanisms in Summarization Evaluation

arXiv:2609.01604v1 Announce Type: new Abstract: LLM-based evaluators of natural language generation (NLG) quality are widely deployed as scoring tools and as automated training signals, yet the intern

CompanionSim: Synthetic Data for Evaluating Anthropomorphism in Human-AI Relationships

arXiv:2609.00250v1 Announce Type: cross Abstract: Many people now see AI systems as not just productivity tools but as social companions. Researchers are eager to study the consequences of AI companio

Delegation Without Trust: An Empirical Gap Analysis of Identity, Authorization, and Runtime Governance in Multi-Agent LLM Systems

arXiv:2609.00267v1 Announce Type: cross Abstract: Autonomous LLM agents increasingly act on a user's behalf: they hold credentials, call tools and services, and spawn sub-agents that act further on th

Energy-Based Transformers as Predictors of Reading Difficulty

arXiv:2606.23382v2 Announce Type: replace-cross Abstract: Transformer language models have become established tools for modeling human sentence processing, with measures such as surprisal and attentio

researcharxiv-cs-ai

EULER: Exploring Underused Links with Evidence-Checked Return for Multi-Agent Mathematical Discovery

arXiv:2609.00032v1 Announce Type: new Abstract: Mathematical communities work with different objects, invariants, and tools, so transferring a problem across them is expensive and often skipped. We pr

GuidedBench: Measuring and Mitigating the Evaluation Discrepancies of In-the-wild LLM Jailbreak Methods

arXiv:2502.16903v3 Announce Type: replace Abstract: Despite the growing interest in jailbreaks as an effective red-teaming tool for building safe and responsible large language models (LLMs), flawed e

HarnessDev: Can LLMs Create and Evolve Their Own Agent Harness?

arXiv:2609.01437v1 Announce Type: cross Abstract: As agents move from research prototypes to deployed tools, their capability increasingly depends on model-external execution infrastructure, commonly

HarnessEvolve: Learning from Reference Trajectories for Reliable Agent Self-Evolution

arXiv:2609.00829v1 Announce Type: cross Abstract: Self-evolving agents advance toward autonomy by optimizing their harness---prompts, skills, tools, and execution logic---based on environmental feedba

LEAP: Likelihood Elicitation and Aggregation for LLM-based Probabilistic Forecasting

arXiv:2609.01337v1 Announce Type: new Abstract: LLM-based forecasting systems have improved on real-world tasks such as financial markets and sports outcomes, largely through stronger search and tool

Applications

No Pixel Left Behind: Filling Gaps in Anime Colorization

arXiv:2609.00800v1 Announce Type: cross Abstract: Animation production workflows often involve digital colorization of line art, where small unpainted regions ('gaps') frequently occur and remain an u

applicationsarxiv-cs-cv

Online camera-pose-free stereo endoscopic tissue deformation recovery with tissue-invariant vision-biomechanics consistency

arXiv:2506.19388v2 Announce Type: replace Abstract: Tissue deformation recovery based on stereo endoscopic images is crucial for tool-tissue interaction analysis and benefits surgical navigation and a

safetyarxiv-cs-cv

Local Ai

Spawn Freely, Act Sparingly: Progressive Risk Vesting for Recursive LLM-Agent Trees

arXiv:2609.01035v1 Announce Type: new Abstract: Recursive LLM agents can broaden their search by spawning specialists. Some branches later request tools that send data or deploy code. When should a br

local-aiarxiv-cs-ai

Topic Matching in the Wild: Benchmark and Lessons from Real-World ASR Transcripts

arXiv:2609.00330v1 Announce Type: cross Abstract: In contact centers, real-time agent-assist tools determine, for each of many predefined topics, whether a live customer utterance is relevant and disp

Towards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness

arXiv:2609.00050v1 Announce Type: cross Abstract: Agentic AI is enabling cloud-based workflows in which autonomous agents reason over operational state, invoke authorized tools, modify software and in

safetyarxiv-cs-ai

TRIAGE: Three-level Routing and Intelligent Agent Guidance for Efficient Execution

model-releasesarxiv-cs-lg

arXiv:2609.01428v1 Announce Type: new Abstract: Large Language Model (LLM) agents based on the ReAct paradigm have demonstrated remarkable capabilities in tool use and task execution. However, ReAct s

Agents in the Large: Perception-Centered Architecture for Persistent Agents

arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a

agentsarxiv-cs-cl

Arkios: An Open Bilingual English-Nepali Language Model Trained From Scratch, with a Devanagari-Aware Tokenizer

arXiv:2608.30092v1 Announce Type: cross Abstract: We present Arkios, a 1.04B-parameter dense transformer pretrained from scratch on 150B tokens of bilingual English-Nepali text, using a custom single-

Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs

arXiv:2601.03087v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit systematic biases across demographic groups. Auditing is proposed as an accountability tool for black-box

safetyarxiv-cs-cl

Development of an Autonomous AI Coding Agent using Monte Carlo Tree Search (MCTS) and Gemini LLM Frameworks

arXiv:2608.29096v1 Announce Type: cross Abstract: The ongoing changes in software engineering requirements have created a substantial need for automated tools which can create secure source code from

Effective Graph and Rank-based Contextual Embeddings for Textual and Multimedia Data

arXiv:2608.29001v1 Announce Type: cross Abstract: In a data-driven world, efficiently organizing and mapping relationships between objects is crucial. Graphs are powerful tools for modeling these conn

researcharxiv-cs-cv

EvoBrowseComp: Benchmarking Search Agents on Evolving Knowledge

arXiv:2606.13120v2 Announce Type: replace Abstract: Search Agents -- large language models augmented with search tools -- have intensified the need for future-proof evaluation benchmarks. Existing ben

EvoGenUI-Bench: Evaluating LLMs as Multi-Turn Generative UI Assistants

arXiv:2608.29387v1 Announce Type: new Abstract: Large language models can generate interactive web interfaces, but reliable generative UI requires maintaining an executable artifact as user requests e

Graph Representational Learning: When Does More Expressivity Hurt Generalization?

arXiv:2505.11298v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) are powerful tools for learning on structured data, yet the relationship between their expressivity and predictive perf

researcharxiv-cs-lg