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What You See Is What You Get: Observation-Aligned Supervision for Chart-to-Code Generation

arXiv:2607.04726v1 Announce Type: new Abstract: Chart-to-code generation is commonly trained with supervised fine-tuning on reference plotting scripts, implicitly treating the gold code as a fully obs

researcharxiv-cs-cl

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Safety

When Agents Lie: Premeditation, Persistence, and Exploitation in Repeated Games

DGX agent

arXiv:2607.05132v1 Announce Type: cross Abstract: As large language models are deployed as autonomous agents that communicate intentions before acting, a critical safety question is whether agents tha

safetyarxiv-cs-cl

7 Jul 2026

When Aggregate Alignment Misleads: Auditing Policy Repair Without Per-State Expert Actions

arXiv:2607.03386v1 Announce Type: new Abstract: Agentic AI systems are increasingly used to edit, refine, and repair decision policies, but evaluating these edits is difficult when per-state expert ac

When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents

arXiv:2607.05189v1 Announce Type: cross Abstract: Persistent personal agents combine long-term memory with access to users' external environments, enabling personalized foreground assistance and proac

When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters

arXiv:2607.04919v1 Announce Type: new Abstract: Deploying a time series foundation model requires GPU infrastructure, engineering overhead, and carries no guarantee of improvement over XGBoost. We pro

When Does High-CFG Diffusion Inversion Fail? A Controlled Study of Prompt--Latent Interactions

model-releasesarxiv-cs-cv

arXiv:2607.04731v1 Announce Type: new Abstract: Text-guided diffusion inversion is central to image editing, where an image is mapped to an initial latent and then edited by replaying the denoising pr

When Does Resolution Help a Frozen Backbone? Global Attention at Resolution Predicts Scalable Adaptation for Camouflaged and Marine Animal Segmentation

arXiv:2607.02708v1 Announce Type: new Abstract: Adapting frozen vision foundation models to fine-grained segmentation now largely depends on backbone selection. Whether the backbone applies global att

When Does Small Data Work? Accuracy and Efficiency Trade-offs Between Tabular Foundation Models and Conventional Methods for Crowd-State Classification at Hajj and Umrah

arXiv:2607.04013v1 Announce Type: cross Abstract: Learning from few labeled examples is a central challenge in tabular machine learning, and it becomes the binding constraint in domains where labeling

When Geometry Aligns: Dihedral Hidden-State Transformations in UNet, ViT, and DiT Architectures

arXiv:2607.03580v1 Announce Type: cross Abstract: Diffusion architectures now encompass convolutional UNets as well as transformer-based designs such as Diffusion Transformers (DiTs), inspired by Visi

When is a System Discoverable from Data? Discovery Requires Chaos

arXiv:2511.08860v2 Announce Type: replace-cross Abstract: The deep learning revolution has spurred a rise in advances of using AI in sciences. Within physical sciences the main focus has been on disco

When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual Try-On

arXiv:2603.05659v3 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) and Rubrics as Rewards (RaR) have driven strong gains in domains with clear correctness

When Simpler Is Better: Evaluating Translation Pipelines for Medieval Latin Manuscripts

arXiv:2607.03836v1 Announce Type: cross Abstract: Despite remarkable progress in machine translation, Vision Language Models (VLMs) struggle on historical manuscripts, a domain that stresses core Natu

When Users Are Happy but Agents Are Wrong: Multi-Dimensional Evaluation of Tool-Augmented Dialogue

model-releasesarxiv-cs-cl

arXiv:2510.19186v3 Announce Type: replace Abstract: Evaluating conversational AI systems that use external tools is challenging, as errors can arise from complex interactions among user, agent, and to

Local Ai

When Words Predict Workload

arXiv:2607.04951v1 Announce Type: cross Abstract: Standard distributed ac{llm} schedulers rely on static token counts or rolling latency averages, making them susceptible to failures on statutorily co

local-aiarxiv-cs-cl

Where do LLMs Fall Short in CBT-Guided Affective Reasoning?

arXiv:2607.02885v1 Announce Type: cross Abstract: Cognitive Behavioral Therapy (CBT) provides a structured framework for understanding a user's mental state by examining the interaction between cognit

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

Who's Behind It? Annotating and Extracting Conspiratorial Actors from German Telegram Posts

arXiv:2607.04962v1 Announce Type: new Abstract: Conspiracy theories commonly attribute important events to the actions of powerful and secretive actors. While computational research has largely focuse

researcharxiv-cs-cl

Why Pure Reasoning is Not Enough: Nature as the Source of Mathematical Innovation

arXiv:2607.04505v1 Announce Type: new Abstract: We advance the hypothesis that human mathematical reasoning, constrained by both the undecidability and the computational intractability of even modest

Applications

Why teaching resists automation in an AI-inundated era: Human judgment, non-modular work, and the limits of delegation

arXiv:2604.07285v2 Announce Type: replace Abstract: Debates about artificial intelligence (AI) in education often portray teaching as a modular and procedural job that can increasingly be automated or

applicationsarxiv-cs-cl

Why3-py: A Tool for Formal Verification of Hypothesis Testing and Meta-Analysis in Python

arXiv:2607.03951v1 Announce Type: cross Abstract: The reproducibility crisis in scientific research has received widespread recognition, thereby increasing the importance of meta-analyses that integra

WildSplat: Feedforward Gaussian Splatting from Unposed In-the-Wild Images

arXiv:2607.05347v1 Announce Type: new Abstract: While feedforward 3D reconstruction excels at efficient novel view synthesis, it typically falters when faced with scenes under varying illumination. To

Safety

WinTA-GIL: Windowed Trajectory Alignment for GNSS-IMU-LiDAR Heading Refinement in Intermittent Signal Environments

arXiv:2607.04879v1 Announce Type: new Abstract: Although multi-source fusion positioning systems have achieved significant progress, accurate and reliable heading estimation remains a critical challen

safetyarxiv-cs-ro

WorldBagel: Uncovering the Power of Unified Multimodal Models for Vision-Language-Action-World Modeling

model-releasesarxiv-cs-cv

arXiv:2607.03461v1 Announce Type: new Abstract: World models aim to capture environment dynamics in ways that support perception, reasoning, and action, and have recently become a central direction in

WorldMesh: Generating Navigable Multi-Room 3D Scenes via Mesh-Conditioned Image Diffusion

arXiv:2603.22972v3 Announce Type: replace Abstract: Recent progress in image and video synthesis has inspired their use in advancing 3D scene generation. However, we observe that text-to-image and -vi

Worldscape-MoE: A Unified Mixture-of-Experts World Model for Scalable Heterogeneous Action Control

arXiv:2607.03964v1 Announce Type: cross Abstract: World models are rapidly becoming a core infrastructure for embodied intelligence and interactive agents: they provide controllable simulators in whic

Local Ai

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection

arXiv:2607.04350v1 Announce Type: new Abstract: Online social media posts provide scalable signals for early depression screening, and recent studies mainly improve pre-classification evidence through

local-aiarxiv-cs-cl

Wrong Before Right: Late Rescue and Interface Failure in Aligned Language Models

model-releasesarxiv-cs-cl

arXiv:2607.04640v1 Announce Type: new Abstract: We study how correctness is assembled inside aligned language models, not only whether the final answer is right. Using layer-wise difference-in-differe

WSA_1: a 3D-Centric World-Spatial-Action Model for Generalizable Robot Control

model-releasesarxiv-cs-ro

arXiv:2607.03941v1 Announce Type: new Abstract: Recent advances in embodied AI have established robot foundation models (RFMs) as the dominant approach for generalist robotic systems to date. By lever

XPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection

model-releasesarxiv-cs-cv

arXiv:2607.03562v1 Announce Type: new Abstract: As deepfake detection models increasingly produce natural language explanations, their reasoning often remains weakly grounded in visual artifacts, limi

XS-VLA: Coupling Coarse-grained Spatial Distillation with Latent Flow Matching for Lightweight Robotic Control

arXiv:2607.04171v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have shown strong multimodal understanding and spatial grounding, but their computational cost limits real-time r

You Frame It: How Conceptual Representations Shape LLM Detection and Reasoning about Antisemitism

arXiv:2607.04945v1 Announce Type: new Abstract: LLMs enable the integration of external conceptual resources at inference time, creating new opportunities for detecting ideologically and historically

researcharxiv-cs-cl

Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses

arXiv:2607.05029v1 Announce Type: cross Abstract: Persistent memory has enabled large language model (LLM) agents to store factual knowledge, prior decisions, reasoning histories, tool usage informati

agentsarxiv-cs-ai

A Convex Obstacle Avoidance Formulation

arXiv:2512.13836v2 Announce Type: replace-cross Abstract: Autonomous driving requires reliable collision avoidance in dynamic environments. Nonlinear Model Predictive Controllers (NMPCs) are suitable

agentsarxiv-cs-ro

A Dual-Helix Governance Approach Towards Reliable Agentic Artificial Intelligence for WebGIS Development

arXiv:2603.04390v2 Announce Type: replace Abstract: WebGIS development requires consistency, yet agentic AI often fails due to LLM context constraints, forgetting, stochasticity, instruction failure,

agentsarxiv-cs-ai

Local Ai

A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention

arXiv:2601.04509v2 Announce Type: replace Abstract: Mixed-integer linear programming (MILP) is a foundational framework for combinatorial optimization across science and engineering, but remains hard

local-aiarxiv-cs-ai

A global predicted-fMRI drive signal from TRIBE does not predict YouTube replay heatmaps

arXiv:2607.01400v1 Announce Type: cross Abstract: Deep multimodal brain-encoding models now predict fMRI responses to naturalistic video with high accuracy. Whether their predicted neural signals also

A Hippocampus for Linear Attention: An Exact Memory for What the Recurrent State Forgets

arXiv:2607.02303v1 Announce Type: new Abstract: Linear-attention and state-space language models compress the prefix into a fixed-size recurrent state, yielding O(1) memory at the cost of a lossy exac

A Mathematical Introduction to Diffusion Models

arXiv:2607.01693v1 Announce Type: new Abstract: These notes give a proof-oriented introduction to diffusion models from the viewpoint of sampling, tracing a single arc from classical sampling dynamics

researcharxiv-cs-lg

A Memory Efficient Unified Algorithm for Online Learning of Linear Dynamical Systems

arXiv:2607.02050v1 Announce Type: new Abstract: Motivated by the challenge of stabilizing a general unknown linear dynamical system (LDS) from observations, we study the natural prerequisite of online

Safety

A More Accurate Algorithm Comparison through A/B Testing using Offline Evaluation Methods

arXiv:2607.01958v1 Announce Type: new Abstract: A/B testing is the gold standard for selecting the better algorithm in online services. While offline evaluation has attracted attention as a safer alte

safetyarxiv-cs-lg

A Multi-Branch Hierarchy-Aware Framework for Heterogeneous Audio Classification

arXiv:2607.01974v1 Announce Type: cross Abstract: This technical report describes our system for Task 1 of the DCASE 2026 Challenge, which aims to classify heterogeneous audio recordings according to

A Novel Machine Learning Approach for Central Nervous System Tumor Classification from DNA Methylation

arXiv:2607.01307v1 Announce Type: new Abstract: NA methylation profiling has become a powerful approach for central nervous system (CNS) tumor classification, yet important challenges remain regarding

researcharxiv-cs-lg

A Practice Auditing Framework for Large Language Model Use: Collective Empiricism, Pseudo-Rational Cognition, and Governance of AI-Generated Content

arXiv:2607.01248v1 Announce Type: cross Abstract: Large language models are increasingly used for knowledge acquisition, code generation, academic writing, and agent-based automation. In these setting

agentsarxiv-cs-ai

A Reconfigurable Rocker-Bogie Robot for High Step Climbing and Turning

arXiv:2607.01554v1 Announce Type: new Abstract: This study proposes a reconfigurable rocker-bogie mechanism that achieves efficient turning motion with a small number of actuators while maintaining hi

researcharxiv-cs-ro

A rubric-based controlled comparison of frontier language models on expert-authored clinical reasoning tasks

arXiv:2607.02175v1 Announce Type: new Abstract: Multiple-choice medical benchmarks are increasingly saturated, and recent rubric-based evaluations such as HealthBench have shown that open-ended clinic

A Stereo Visual SLAM System Using Object-Level Motion Estimation and Geometric Filtering Based on Cross Disparity

arXiv:2607.02005v1 Announce Type: new Abstract: This paper presents OCD SLAM, a dynamic stereo visual SLAM framework that extends ORB-SLAM2 by jointly addressing dynamic objects and dynamic features i

researcharxiv-cs-ro

A Storm-Centric 250 m NEXRAD Level-II Dataset for High-Resolution ML Nowcasting

arXiv:2510.16031v2 Announce Type: replace-cross Abstract: Machine learning-based precipitation nowcasting relies on high-fidelity radar reflectivity sequences to model the short-term evolution of conv

researcharxiv-cs-lg

Tutorials

A Survey of Circuit Foundation Model: Foundation AI Models for VLSI Circuit Design and EDA

arXiv:2504.03711v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI)-driven electronic design automation (EDA) techniques have been extensively explored for VLSI circuit design appli

tutorialsarxiv-cs-lg