Search: “research”

arXiv:2607.20592v1 Announce Type: new Abstract: Spatio-temporal machine-learning modelling is an important tool in environmental research. However, machine-learning models are highly sensitive to both

tutorialsarxiv-cs-lg

24 Jul 2026

A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs

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DGX agent

arXiv:2607.17075v2 Announce Type: replace-cross Abstract: The advent of LLMs has significantly changed the research on privacy policy and data compliance analysis by enabling tasks that previously req

model-releasesarxiv-cs-cl

23 Jul 2026

Abstraction Induces the Brain Alignment of Language and Speech Models

arXiv:2602.04081v2 Announce Type: replace Abstract: Research has repeatedly demonstrated that intermediate hidden states extracted from large language models and speech audio models predict measured b

Great X: A Unified Multi-Modal Simulator Bridging the Sim2Real Gap for 6G

arXiv:2507.08716v4 Announce Type: replace Abstract: Large-scale, precisely synchronized multi-modal datasets are critical for data-driven sixth-generation (6G) wireless research, yet real-world collec

safetyarxiv-cs-cv

Local Ai

The Giant Hippocampus: From Structural Monoculture to a System of Systems

arXiv:2607.19973v1 Announce Type: new Abstract: AI researchers describe state-of-the-art models as one thing repeated at scale: the Transformer, wired identically for text, pixels, or speech. Neurosci

local-aiarxiv-cs-ai

TINY_SCHILLER: A Drop-In German Drama Corpus for Small Language Models

arXiv:2607.19992v1 Announce Type: cross Abstract: tiny_schiller closes the small-language-model prototyping, fine-tuning, education, and research gap for German literary text, providing a single-file,

applicationsarxiv-cs-ai

A Generalised Exponentiated Gradient Approach to Enhance Fairness in Binary and Multi-class Classification Tasks

arXiv:2603.21393v2 Announce Type: replace Abstract: The widespread use of AI and ML models in sensitive areas raises significant concerns about fairness. While the research community has introduced va

safetyarxiv-cs-lg

M2P-AD: Memory-to-Prototype Learning with Boundary-aware Score Refinement for 3D Anomaly Detection

arXiv:2607.13499v1 Announce Type: new Abstract: 3D anomaly detection has recently emerged as an important research topic in computer vision. Although existing methods have achieved high performance, e

applicationsarxiv-cs-cv

Networked Intelligence: Active Shared Context Graphs for Human-AI Team Science

arXiv:2607.13220v1 Announce Type: new Abstract: Most AI-for-science systems focus on scaling a single reasoning process through better models, larger context windows, long-horizon agentic execution, o

Pretraining in Actor-Critic Reinforcement Learning for Locomotion

arXiv:2510.12363v4 Announce Type: replace-cross Abstract: The pretraining-finetuning paradigm has facilitated numerous transformative advancements in artificial intelligence research in recent years.

safetyarxiv-cs-lg

Securing LLMs in the Wild: Privacy and Security Challenges at the Edge

model-releasesarxiv-cs-lg

arXiv:2607.13088v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly moving from research settings into the wild, deployed on enterprise infrastructure, personal devices, and edg

Self-Improvements in Modern Agentic Systems: A Survey

arXiv:2607.13104v1 Announce Type: new Abstract: Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, fro

AdaPCLA: Adaptive Prior-Calibrated Logit Adjustment for Long-Tailed Longitudinal EHR Generation

arXiv:2607.12645v1 Announce Type: new Abstract: Generative modeling of longitudinal Electronic Health Records is increasingly important for privacy-preserving research, yet standard autoregressive mod

applicationsarxiv-cs-lg

Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction

arXiv:2607.12835v1 Announce Type: new Abstract: Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, whe

Directional Constraints for Efficient Exploration in Safe Reinforcement Learning

arXiv:2607.12784v1 Announce Type: cross Abstract: Reinforcement Learning has revolutionized the landscape of robotic research, allowing robust learning of complex robotic skills in simulation. However

safetyarxiv-cs-lg

Silent Alarm: A J-Space Protocol for Comparing Danger Recognition Across Models and Quantization Levels

arXiv:2607.12792v1 Announce Type: cross Abstract: Jailbreak-robustness research typically evaluates safety through generated responses using an LLM-as-judge approach. Such evaluations, however, are se

So Many Opinions, So Many LLMs: Comparing Large Language Models to Traditional Machine Learning for Open- Ended Survey Analysis

arXiv:2607.11890v1 Announce Type: cross Abstract: Open-ended surveys offer valuable insights, but they are notoriously difficult to analyze at scale. Building on previous work that employed traditiona

The Capacity of Thought: Benchmarking Llama 3.2 in Semantic fMRI Neural Language Decoding and Improving the Huth Encoding-Model Baseline

model-releasesarxiv-cs-cl

arXiv:2607.12079v1 Announce Type: new Abstract: Decoding continuous language from fMRI signals remains a core challenge in non-invasive brain-computer interface research. We present two complementary

Tracing Agentic Failure from the Flow of Success

arXiv:2607.12747v1 Announce Type: new Abstract: Failure attribution for LLM-based agentic systems, i.e., identifying which steps in a failure trajectory caused the task to fail, is critical for debugg

VanillaBench: The Hidden Accuracy Cost of Adversarial Robustness

model-releasesarxiv-cs-cv

arXiv:2607.12545v1 Announce Type: cross Abstract: Adversarial robustness research has produced hundreds of defended models over the past decade, yet the literature almost universally reports robustnes

ViHoRec: A Quality-Controlled Vietnamese Hotel Recommendation Dataset and Cold-Start Benchmark

arXiv:2607.12946v1 Announce Type: cross Abstract: Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a res

Win by Silence: Deletion Non-Monotonicity, Autonomous Exploitation, and Typed-State Gating in LLM Plan Evaluation

arXiv:2607.12986v1 Announce Type: new Abstract: Plan evaluators can reward a strategic plan for becoming less explicit. This paper studies that failure in a staged expected-value scorer for LLM-genera

Hardware

ARGUS: Accelerated, Robust, General, and Unsupervised Cell Tracking Solutions

arXiv:2607.08297v1 Announce Type: new Abstract: Background and Objective: Quantitative analysis of cell dynamics is central to modern biological research, providing critical insights into immune cell

hardwarearxiv-cs-cv

Efficient Safety Alignment of Language Models via Latent Personality Traits

arXiv:2607.07918v1 Announce Type: cross Abstract: Current safety methods for large language models are known to be vulnerable to adversarial attacks, motivating research into robust alternatives. Late

safetyarxiv-cs-ai

Feedback Manipulation Regularization: Enabling Offline Agent Alignment for Imitation Learning

arXiv:2607.07859v1 Announce Type: new Abstract: Reinforcement learning (RL) research has increasingly shifted focus towards alignment, ensuring agents learn behaviors adhering to human values. While h

safetyarxiv-cs-ai

Idiobionics: The Unification of Privacy and Intelligent Robotic Prostheses

arXiv:2607.07775v1 Announce Type: new Abstract: The human body is at the center of a growing family of technologies designed to tightly and persistently couple biological and digital systems. Robotic

IFAR: Multi-Perspective and Multi-Level Causal Discovery with LLMs

arXiv:2409.05559v2 Announce Type: replace Abstract: Large language models (LLMs) have developed rapidly, and their reasoning capabilities have become a hot research topic. However, there is still limi

Multi-agent Autoformalization of Tensor Network Theory

arXiv:2607.07857v1 Announce Type: cross Abstract: We build a team of specialized large language-model agents and present an agent-driven workflow for research-level formalization in theoretical physic

Reinforcing the Generation Order of Multimodal Masked Diffusion Models

arXiv:2607.08056v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that a

Scalable and Culturally Specific Stereotype Dataset Construction via Human-LLM Collaboration

arXiv:2607.07895v1 Announce Type: new Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages

Validating LLMs in social science: Epistemic threats and emerging norms

arXiv:2607.07915v1 Announce Type: cross Abstract: Large language models (LLMs) are reshaping social science methodology. Researchers increasingly prompt language models to generate quantitative measur

Security and Privacy in Agentic AI: Grand Challenges and Future Directions

arXiv:2607.06608v1 Announce Type: cross Abstract: We present key challenges and future research directions in the security and privacy of agentic AI, based on a horizon-scanning exercise that brought

9 Jul 2026

Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms

arXiv:2607.06489v1 Announce Type: new Abstract: The dairy industry in Ireland has a large potential for the integration of renewable energy and the reduction of carbon emissions. However, researchers

8 Jul 2026

Local Ai

Patch Knowledge Transfer for Efficient AI-Generated Image Quality Assessment

arXiv:2607.05605v1 Announce Type: new Abstract: With the rapid advancement of image generation technologies, perceptual quality assessment of AI-generated images has emerged as a crucial research dire

local-aiarxiv-cs-cv

8 Jul 2026

UniField: A Unified Field-Aware MRI Enhancement Framework

arXiv:2603.09223v2 Announce Type: replace Abstract: Magnetic Resonance Imaging (MRI) field-strength enhancement holds immense value for both clinical diagnostics and advanced research. However, existi

safetyarxiv-cs-cv

8 Jul 2026

Agent Data Injection Attacks are Realistic Threats to AI Agents

arXiv:2607.05120v1 Announce Type: cross Abstract: AI agents act on behalf of user prompts, consuming external data and taking actions based on the agent context. Prior research on AI agent security ha

CoorGrasp: Coordinated Contact Control for Adaptive Dexterous Grasping Under Uncertainty

arXiv:2607.03557v1 Announce Type: new Abstract: While recent research has focused heavily on dexterous grasp pose generation, less attention has been devoted to the execution of planned grasps. Under

applicationsarxiv-cs-ro

Equivalence of Context and Parameter Updates in Modern Transformer Blocks

model-releasesarxiv-cs-lg

arXiv:2511.17864v3 Announce Type: replace Abstract: Recent research has established that the impact of context in a vanilla transformer can be represented implicitly by forming a token-dependent, rank

FOI-O: An NZ-first ontology and verification methods package for Freedom of Information process modelling

arXiv:2607.02947v1 Announce Type: cross Abstract: Public official-information request records contain process signals. They can support research, workflow review, and human-supervised agent help. Yet

agentsarxiv-cs-cl

Ghosts Beneath Textures: Texture-Relation Cues for Cross-Paradigm AI-Generated Image Detection

model-releasesarxiv-cs-cv

arXiv:2607.03862v1 Announce Type: new Abstract: AI-generated images have proliferated rapidly, motivating extensive research. Most existing AI-generated image detectors are developed and evaluated und

Invisible Strings: Deriving Puppetry Principles and their Hidden Connections to Robot Behavior Design

arXiv:2607.03289v1 Announce Type: new Abstract: When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these

applicationsarxiv-cs-ro

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training

model-releasesarxiv-cs-cv

arXiv:2602.06285v2 Announce Type: replace Abstract: Recent research in geospatial machine learning has demonstrated that models pretrained with self-supervised learning on Earth observation data can p

OptiAgent: End-to-End Optimization Modeling via Multi-Agent Iterative Refinement

arXiv:2607.05346v1 Announce Type: new Abstract: We propose OptiAgent, a multi-agent framework that, given a natural language description of an Operations Research problem, is able to output a solver-r

Rethinking Scientific Discovery in an Agentic Era

arXiv:2607.03863v1 Announce Type: new Abstract: Artificial intelligence has advanced scientific discovery, but most AI4Science systems remain fragmented tools that rely on humans to coordinate problem

agentsarxiv-cs-cl

Hardware

SPORK: Self-Speculative Forking to Accelerate Agentic LLM Inference

arXiv:2607.03333v1 Announce Type: cross Abstract: LLM agents are becoming a common interface for research, coding, and question answering, yet their Thought-Action-Observation loop is often serial: th

hardwarearxiv-cs-ai

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks

arXiv:2510.16923v3 Announce Type: replace-cross Abstract: Deep learning models deployed in safety critical applications like autonomous driving use simulations to test their robustness against adversa

safetyarxiv-cs-ai

Unveiling the Unborn: Advancing Fetal Health Classification through Machine Learning

arXiv:2310.00505v3 Announce Type: replace-cross Abstract: Fetal health classification is a critical task in obstetrics, enabling early identification and management of potential health problems. Howev

applicationsarxiv-cs-ai

Which Algorithm Specification Formats Help Language Models Implement Machine Learning Algorithms?

arXiv:2607.03158v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to implement algorithms from research manuscripts, but papers often leave implementation choices im