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Terminal Agents Suffice for Enterprise Automation

arXiv:2604.00073v3 Announce Type: replace-cross Abstract: There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomousl

Test, then Route: How Language Models Execute In-Context Conditional Rules Across Models and Languages

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DGX agent

arXiv:2608.04183v1 Announce Type: new Abstract: When a language model follows an in-context conditional rule such as 'if P(x) then A else B,' does it assemble a runtime circuit with one module that te

model-releasesarxiv-cs-cl

6 Aug 2026

Text2GraphQuery-Bench: A Text to Graph Query Benchmark

arXiv:2602.11745v2 Announce Type: replace Abstract: Graph models are fundamental to data analysis in domains rich with complex relationships. Unlike SQL, which benefits from a rel- atively unified sta

The Calibration Floor: Format Repair Can Masquerade as Self-Correction at Small-to-Mid Scale

arXiv:2608.04355v1 Announce Type: new Abstract: Accuracy changes after language-model self-revision are usually interpreted as changes in reasoning. We show this can fail at the answer-extraction boun

The Cost of Binarizing Survival Outcomes in Clinical Prognostic Modeling

arXiv:2608.04046v1 Announce Type: cross Abstract: Survival analysis is an established framework for analyzing time-to-event data, yet many clinical machine learning studies still binarize the outcome

The Effect of Perceived Race and Gender on Police Language Use: Experimental Evidence from VR Simulations

arXiv:2608.05050v1 Announce Type: cross Abstract: Against the backdrop of violence in police interactions with the U.S. public, we explore how deferentially police officers speak to virtual characters

researcharxiv-cs-ai

The Evaluator Is Part of the Experiment: Measuring Open-Ended LLM Conformity

arXiv:2608.04463v1 Announce Type: new Abstract: Prior work on LLM conformity largely measures discrete answer flips under verifiable labels. Open-ended revisions require a different measurement strate

The Fairness Collapse Phenomenon: Bias Amplification in Language Models Trained on Synthetic Data

arXiv:2608.04268v1 Announce Type: new Abstract: Generative models trained on artificially generated data have been shown to exhibit model collapse, resulting in significant performance degradation. As

safetyarxiv-cs-cl

The First EgoCross Challenge at EgoVis 2026: Cross-Domain Egocentric Video Question Answering

arXiv:2608.04589v1 Announce Type: cross Abstract: EgoCross is a cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize

The LLM Proposes, the Executive Disposes: A Self-Verifying Agent Instrument that Dissociates Commitment Drift from Binding Drift in Long-Horizon Agents

arXiv:2608.04066v1 Announce Type: new Abstract: How do you verify a long-horizon agent when its own state and self-reports are exactly what you cannot trust? We present an agent instrument built so th

The Loss Does Not See the Basis, but Adam Does

model-releasesarxiv-cs-lg

arXiv:2608.05136v1 Announce Type: new Abstract: Gradient descent on a factored model W = UV^op is implicitly biased toward low-rank solutions, while Adam, starting from the same small initialization,

Local Ai

The Neural Echo: A Signal Processing Perspective for Understanding Neural Networks

arXiv:2608.04864v1 Announce Type: cross Abstract: We introduce the neural echo as a tool for understanding the behavior of neural networks. It generalizes the model-based concepts of impulse responses

local-aiarxiv-cs-lg

The Order Is the Guarantee: Verifier-Budgeted Code Deletion with Static-First Learned Proposals

arXiv:2608.04611v1 Announce Type: cross Abstract: Frontier coding models now match or exceed strong human reference points on programming benchmarks, yet benchmark success does not imply maintainable

The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads

arXiv:2608.04570v1 Announce Type: new Abstract: Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inferenc

researcharxiv-cs-cl

Applications

The Price of Isolation: Estimating the Ecosystem Cost of Symmetric Two-Sided A/B Testing

arXiv:2608.04432v1 Announce Type: cross Abstract: On two-sided content platforms, symmetric two-sided isolation (assigning matched fractions of creators and viewers to isolated treatment and control s

applicationsarxiv-cs-lg

Tutorials

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis

tutorialsarxiv-cs-ai

The Sample Complexity of Distributionally Robust PAC Learning under Cressie--Read Divergences

arXiv:2608.04686v1 Announce Type: new Abstract: We study distributionally robust PAC learning for the 0--1-loss, where adversarial perturbations of the data distribution are constrained by a Cressie--

The Yokai Learning Environment: Tracking Beliefs Over Space and Time

arXiv:2508.12480v3 Announce Type: replace Abstract: The ability to cooperate with unknown partners is a central challenge in cooperative AI and widely studied in the form of zero-shot coordination (ZS

Thinking with Anchors: Grounded and Efficient Document Reasoning

model-releasesarxiv-cs-cv

arXiv:2608.04424v1 Announce Type: new Abstract: Existing document understanding benchmarks have largely focused on locating page elements, yet real-world document intelligence requires models to reaso

TIDE: A Physically Diverse 3D Turbulence Benchmark Dataset for Advancing Scientific Machine Learning

model-releasesarxiv-cs-lg

arXiv:2608.04222v1 Announce Type: cross Abstract: Turbulence is a central testbed for machine learning on physical dynamics because its governing laws are known exactly. However, most existing studies

ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation

arXiv:2608.04436v1 Announce Type: new Abstract: Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understandi

safetyarxiv-cs-cv

TopoChunker: Topology-Aware Agentic Document Chunking Framework

arXiv:2603.18409v2 Announce Type: replace Abstract: Current document chunking methods for Retrieval-Augmented Generation (RAG) typically linearize text. This forced linearization strips away intrinsic

agentsarxiv-cs-cl

TourSynbio-Search: A Large Language Model Driven Agent Framework for Unified Search Method for Protein Engineering

arXiv:2411.06024v1 Announce Type: cross Abstract: The exponential growth in protein-related databases and scientific literature, combined with increasing demands for efficient biological information r

Toward Federated Large Language Models in Medicine: A Parameter-Efficient Framework for Privacy-Preserving, Multi-Institutional Adaptation

arXiv:2601.22124v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly adapted for medical applications, but most are trained using data from a single institution because pr

Toward Integrating Adaptive Experience Replay and Online Uncertainty Estimation in Safe Actor-Critic Optimal Control

arXiv:2608.04732v1 Announce Type: cross Abstract: Safe actor-critic control often treats barrier filtering, uncertainty estimation, and experience replay as separate modules, even though each changes

Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning

arXiv:2608.05139v1 Announce Type: new Abstract: Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivat

Towards a New Grammar of Reasoning for Artificial Legal Intelligence and the Mecelle as Its Semantic Protocol

arXiv:2608.04011v1 Announce Type: cross Abstract: This article examines the enduring epistemic and methodological crisis of traditional legal practice in light of the opportunities and constraints int

Towards a satellite image manipulation and deepfake localization benchmark dataset

arXiv:2608.04840v1 Announce Type: cross Abstract: Verifying the authenticity of satellite imagery has become increasingly critical given advances in generative artificial intelligence. Highly realisti

Towards End-to-End Multilingual Metaphor Processing: Integrating Detection, Translation, and Evaluation

arXiv:2608.04260v1 Announce Type: new Abstract: Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require r

researcharxiv-cs-cl

Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes

arXiv:2608.05000v1 Announce Type: new Abstract: Vision offers a critical axis for advancing foundation models, driving a shift towards natively unified multimodal pretraining. Despite this momentum, t

safetyarxiv-cs-cv

Towards Trustworthy Hypergraph Neural Networks under Label Noise

arXiv:2608.04377v1 Announce Type: cross Abstract: Hypergraph neural networks (HGNNs) have demonstrated remarkable capabilities in processing complex higher-order relationships. However, their performa

Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin

arXiv:2502.15952v3 Announce Type: replace Abstract: Recent works exploring the training dynamics of homogeneous neural network weights under gradient flow with small initialization have established th

Towards Valid B-Rep Generation: Training-Free Wireframe Anomaly Detection and Repair

arXiv:2608.04955v1 Announce Type: new Abstract: Multi-stage boundary representation (B-Rep) generation leverages intermediate wireframes to synthesize CAD models. However, geometric and topological ri

researcharxiv-cs-cv

Local Ai

Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs

arXiv:2608.04759v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inc

local-aiarxiv-cs-cl

Traceable LLM-Generated Hazard Scenarios for Operational Safety Analysis of Aviation Systems Using ASRS Reports

arXiv:2608.04697v1 Announce Type: new Abstract: Operational hazard analysis of aviation system operations must consider interactions among weather, ATC actions, airspace constraints, aircraft operatio

safetyarxiv-cs-ai

Training Crossroads for Recurrent Vision Transformers: Recurrence, Neural ODEs, and Deep Supervision

model-releasesarxiv-cs-cv

arXiv:2608.04879v1 Announce Type: cross Abstract: Vision Transformers (ViTs) achieve strong image-recognition performance, but their parameter count grows linearly with depth when each block is indepe

Local Ai

Training-Free Hashing-Based Attention via Binary Principal Components

arXiv:2608.04405v1 Announce Type: cross Abstract: Long-context large language models (LLMs) are increasingly deployed in real-world applications, yet self-attention remains a major efficiency bottlene

local-aiarxiv-cs-ai

Transfer Learning for Named Entity Recognition of Classical Latin through LLM Prompting

arXiv:2608.04015v1 Announce Type: new Abstract: With the increase in digitized resources of Classical Latin texts and modern breakthroughs of Large Language Models (LLMs), I contribute to ancient lang

Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling

arXiv:2608.04230v1 Announce Type: cross Abstract: Deep learning models for scientific spatio-temporal downscaling often minimize reconstruction error while failing to preserve physically meaningful mu

researcharxiv-cs-cv

TRCoRSurg: Temporal-Relational Co-Reasoning for Surgical Video Triplet Recognition

arXiv:2608.04606v1 Announce Type: new Abstract: Understanding complex surgical scenes requires recognizing multiple interdependent entities, such as instruments, actions, and targets, while maintainin

researcharxiv-cs-cv

TriCLE: Tri-Modal Vision-Language Reasoning for Edge-Deployed Fine-Grained Clustering

arXiv:2608.04175v1 Announce Type: new Abstract: Edge platforms used for aerial observation must interpret aircraft imagery under limited memory, limited compute, and intermittent connectivity. This se

safetyarxiv-cs-cv

Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)

arXiv:2608.04317v1 Announce Type: cross Abstract: Autonomous cyber defense systems based on Deep Reinforcement Learning (DRL) have attracted significant research attention, yet remain evaluated almost

TRNet: Topography-Guided Frequency Rectification and Structure-Aware Decoding for Multimodal Paddy Rice Segmentation

arXiv:2608.04154v1 Announce Type: cross Abstract: Mapping paddy rice from very-high-resolution imagery in mountainous and hilly regions is difficult because terrain alters optical appearance and incre

researcharxiv-cs-ai

Tropical Algebraic Geometry for Neuronal Representations: An Arakelov-Green Measure Based Descriptor for Graph Learning

arXiv:2608.04460v1 Announce Type: cross Abstract: The quantitative analysis of 3D neuronal morphologies requires capturing both graph topology and spatial geometry. Current message-passing Graph Neura

TS2TabPFN: Time Series Classification and Extrinsic Regression through Feature Extraction and a Tabular Foundation Model

arXiv:2608.04174v1 Announce Type: new Abstract: Time series data are ubiquitous in practical applications, where classification (TSC) and extrinsic regression (TSER) have emerged as essential tasks fo

TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction

arXiv:2608.04453v1 Announce Type: cross Abstract: Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map con

Two-Level Meta-Rubrics for Evaluating Open-Ended Generation: GAMUT, a Benchmark for Factual Completeness

arXiv:2607.19322v2 Announce Type: replace Abstract: Rubric-based evaluation of open-ended generation faces a fundamental tension between expressiveness and reliability. Authoring a faithful rubric req

Applications

UBLLIE: Unified Backlight and Low-Light Image Enhancement

arXiv:2608.04429v1 Announce Type: new Abstract: Backlit and low-light images often suffer from severe exposure imbalance or global underexposure, presenting significant challenges for both visual perc

applicationsarxiv-cs-cv