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Discovering Relationships in Data Lakes Using Large Language Models: An Industrial Case

arXiv:2608.26750v1 Announce Type: new Abstract: Data lakes rely on metadata to remain usable, yet this meta data is often limited or weakly informative for column relationship discovery, especially in

researcharxiv-cs-ai

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Disentangling Optimization Scale from Preference Scale in DPO

DGX agent

arXiv:2608.27032v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) is a widely used objective for aligning language models from preference data, with the coefficient eta commonly int

safetyarxiv-cs-lg

28 Aug 2026

Dispersive Forward Tree Search for Optimal Control: Coverage, Complexity, and Computation

arXiv:2608.26314v1 Announce Type: new Abstract: Steering-based planners require solutions to state-to-state boundary value problems, which can be inaccessible for nonlinear platforms. Forward propagat

researcharxiv-cs-ro

Distributed Training using an Intelligent Network

model-releasesarxiv-cs-lg

arXiv:2608.26453v1 Announce Type: new Abstract: Distributed training across a wide area network (WAN) is challenging, as continuous parameter exchange by islands of compute is constrained by limited b

District-Level Food Environment Indicators and Social Vulnerability in Sao Paulo

arXiv:2608.26299v1 Announce Type: cross Abstract: Urban food environments may reflect broader socioeconomic inequalities, but district-level evidence remains limited in Brazilian cities. This study ex

researcharxiv-cs-lg

Do Coding Agents Need Executable World Models, Simplification, and Verification to Solve ARC-AGI-3?

arXiv:2607.15439v2 Announce Type: replace Abstract: Our previous ARC-AGI-3 agent bundled executable world modeling, prompted simplification, and exact replay verification, leaving their individual con

Do Language Models Follow Occam's Razor? An Evaluation of Parsimony in Inductive and Abductive Reasoning

arXiv:2509.03345v3 Announce Type: replace Abstract: Non-deductive reasoning, encompassing inductive and abductive reasoning, is essential in addressing complex real-world questions. One key feature of

agentsarxiv-cs-ai

Do LLMs Understand Personality? Rethinking Persona Fidelity Evaluation through Structured Behavioral Inference

arXiv:2608.26674v1 Announce Type: cross Abstract: As large language models are increasingly deployed to simulate diverse human characters, ensuring persona fidelity, defined as the extent to which an

agentsarxiv-cs-ai

DocTalkBN: A Novel Dataset of Expert Telemedicine Conversations in Bengali

arXiv:2608.27110v1 Announce Type: new Abstract: Reliable medical conversational AI requires authentic expert--patient interaction data, yet such datasets remain scarce, especially for low-resource lan

DOD-SA: Infrared-Visible Decoupled Object Detection with Single-Modality Annotations

arXiv:2508.10445v2 Announce Type: replace Abstract: Infrared-visible object detection has shown great potential in real-world applications, enabling robust all-day perception by leveraging the complem

applicationsarxiv-cs-cv

Tutorials

Domain-Specific Self-Supervised Representation Learning for Retinal Fundus Classification

arXiv:2608.26686v1 Announce Type: new Abstract: Despite the growing number of public datasets, annotated medical images remain scarce. Supervised learning methods achieve strong performance on many be

tutorialsarxiv-cs-cv

Don't Overthink, Don't Underthink: Toward Adaptive Reasoning in Agentic AI

arXiv:2608.26442v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have shown that increased inference-time reasoning can improve performance on complex tasks. However, ma

Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learning

arXiv:2608.26901v1 Announce Type: cross Abstract: Automating prostate radiotherapy treatment planning is dosimetrically complex, particularly for extreme hypofractionated regimens. In this study, we i

researcharxiv-cs-cv

Double Trouble: Bilingual Pretraining Leaves Language-Conditioned Effects in Shared-Language Representations

arXiv:2608.26576v1 Announce Type: new Abstract: When researchers compare multilingual models for probing, interpretability, or cross-lingual transfer, they often align embedding spaces and assume that

DPA-I2P: Depth-Guided Projective Alignment for Image-to-Point-Cloud Registration in Autonomous Driving

arXiv:2608.26589v1 Announce Type: new Abstract: Image-to-Point Cloud Registration aims to estimate the camera pose of a given image within a 3D scene point cloud, which is a fundamental task in autono

safetyarxiv-cs-cv

DRL: A Deterministic Relational Middleware Layer for Transaction-Safe Enterprise NL2SQL Under Schema-Graph Scaling

arXiv:2608.26172v1 Announce Type: cross Abstract: Deploying natural-language interfaces over enterprise OLTP catalogs fails at scale because semantic parsers collapse under schema-graph scaling, infla

Local Ai

DSA: Evidence-Aware LLM-Agent Orchestration for Multi-Market Stock Research

arXiv:2608.26990v1 Announce Type: new Abstract: Large language models can summarize financial information, but an operational stock-research system must first assemble heterogeneous evidence, expose u

local-aiarxiv-cs-ai

DuMateBench: Evaluating Autonomous Agents in Complex Real-World Workflows

arXiv:2608.26546v1 Announce Type: new Abstract: Autonomous agents are increasingly adopted to complete complex, multi-tool workflows in real-world settings. However, existing benchmarks typically sepa

Dynamic Haven Selection for Multi-Agent Pickup and Delivery in Constrained Warehouses

arXiv:2608.26939v1 Announce Type: cross Abstract: Space-efficient warehouse layouts often contain single-agent-width aisles and dead-end workstations where robots have few places to wait without block

agentsarxiv-cs-ro

Dynamical phase selection controls compute scaling in looped transformers

model-releasesarxiv-cs-lg

arXiv:2608.26556v1 Announce Type: cross Abstract: A looped transformer performs inference by iterating a weight-tied map, making its computation a dynamical process whose cost is set by the resulting

EditaLive! Unified Character Video Editing for Live Streaming

arXiv:2608.27123v1 Announce Type: new Abstract: Conventional video editing primarily focuses on scene-level content, whereas live streaming places greater emphasis on the human subject. However, direc

researcharxiv-cs-cv

EduRiskX: A Neuro-Symbolic Framework with F-Logic Reasoning for Early Academic Risk Prediction

arXiv:2608.26107v1 Announce Type: new Abstract: Predicting students' academic risk in online education is crucial for enabling timely interventions that can improve retention and learning outcomes. Ho

applicationsarxiv-cs-ai

EEG-to-Report: An Annotation and Feature-Text Framework for Training Language Models on Clinical EEG

arXiv:2608.26153v1 Announce Type: new Abstract: Clinical electroencephalography (EEG) reporting remains largely manual and time-consuming, and current EEG software ecosystems do not produce the struct

researcharxiv-cs-ai

Egosurg: Arbitrary view synthesis for egocentric replay of operating room workflows from ambient cameras

arXiv:2510.04802v2 Announce Type: replace-cross Abstract: Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric perspectives that shape c

safetyarxiv-cs-ai

ElementCheck: Complexity-Aware Long-Form Text Factuality Evaluation via Sentence Elements

arXiv:2608.26118v1 Announce Type: new Abstract: Existing long-form factuality evaluation relies on the decompose-retrieve-verify pipeline. However, the pipeline suffers from noise from claim decomposi

Embodied Scene Rearrangement Planning

model-releasesarxiv-cs-ro

arXiv:2608.27371v1 Announce Type: new Abstract: This paper introduces Embodied Scene Rearrangement Planning (ESRP), a novel task requiring embodied agents to rearrange furniture in 3D scenes to match

Emotional Preferences as Goal-Priority Regulation

arXiv:2608.27072v1 Announce Type: cross Abstract: A core question in decision-making for agents is whether the relative priorities of competing lower-level objectives can be determined by emotional pr

safetyarxiv-cs-ai

Enforcing Dirichlet Boundary Conditions in Operator Learning

arXiv:2608.27256v1 Announce Type: cross Abstract: Operator learning in scientific machine learning is concerned with approximation of maps between infinite-dimensional function spaces; such maps frequ

researcharxiv-cs-lg

Equal Ranking Quality, Different Decisions: Training Order-Consistent LLM Scorers

arXiv:2608.26762v1 Announce Type: new Abstract: Rerankers, reward models and multi-document QA scorers score candidate documents or responses in one LLM prompt, so each score depends on their order. S

researcharxiv-cs-cl

Evaluating AI Generated Summaries for Cancer Patients

arXiv:2608.26154v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into digital health platforms to generate summaries of complex medical data. Although t

safetyarxiv-cs-ai

Evaluating Confidence-Gated Retrieval with Matched Trajectory Replay

arXiv:2608.26846v1 Announce Type: cross Abstract: Interactive language-model agents use confidence signals to decide whether to answer immediately, retrieve additional evidence (from memory or externa

Evaluating human and LLM screening workflows in a conceptually complex scoping review: Recall--workload trade-offs and run-to-run consistency

arXiv:2608.26885v1 Announce Type: new Abstract: Background. Large language models (LLMs) are increasingly used for screening in evidence synthesis, where false negatives can remove relevant studies be

Evaluating Language Models in Realistic Conversational Contexts

arXiv:2608.26131v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed to serve open-ended, multi-turn interactions, evaluating conversational quality at human scale

Evaluator-Dependent Patient-Adaptive ECG Lead-Channel Allocation

arXiv:2608.26827v1 Announce Type: new Abstract: Patient-conditioned acquisition policies for ECG lead-channel selection can outperform population-wide fixed protocols by tailoring the channel budget t

safetyarxiv-cs-cv

Explainable Artificial Intelligence for Customer Churn Prediction in Telecommunications: A Framework for CRM Integration

arXiv:2608.26151v1 Announce Type: new Abstract: Subscriber attrition is a costly, persistent challenge for telecommunications providers, with monthly churn of roughly 1.9% in mature markets eroding bi

Exploring the Role of LLMs in HPC Programming: A Survey

arXiv:2608.26110v1 Announce Type: cross Abstract: Large Language Models (LLMs) are emerging as promising assistants in High-Performance Computing (HPC), where programming remains complex and expertise

applicationsarxiv-cs-ai

Local Ai

Fairness Invariants: A Relational Approach to Explaining and Mitigating Fairness Bugs

arXiv:2608.26209v1 Announce Type: cross Abstract: Data-driven software systems are increasingly deployed in high-stakes socio-economic domains, from criminal justice to financial lending. However, the

local-aiarxiv-cs-ai

FaithSieve: Fine-Grained Evaluation of Math Proofs with Faithful Formal Evidence

arXiv:2608.26310v1 Announce Type: new Abstract: Large language models can now generate complex, multi-step mathematical proofs, but reliably determining their correctness and localizing early logical

FAN-LoRA: A Fourier-Adaptive Nonlinear Low-Rank Adaptor for Medical Foundation Model Domain Adaptation

model-releasesarxiv-cs-cv

arXiv:2608.26531v1 Announce Type: new Abstract: The advent of vision foundation models, notably the Segment Anything Model (SAM), has catalyzed significant advancements in natural image segmentation.

FaulT-Bench: Towards Benchmarking Network Troubleshooting LLM Agents under Unreliable User Tickets

arXiv:2608.27021v1 Announce Type: cross Abstract: LLM-based agents are increasingly proposed for network fault diagnosis, but existing benchmarks evaluate them only on accurate tickets and always assu

FaultLens: Learning Compact Behavioral Test Suites for Generated Operational Programs

arXiv:2608.26746v1 Announce Type: cross Abstract: Generated operational programs are often validated with either a few hand-written examples or exhaustive regression suites. The former can miss sparse

researcharxiv-cs-ai

Tutorials

Feature Transformation Enhanced Jacobi Polynomial Graph Filtering for Graph Anomaly Detection

arXiv:2608.27144v1 Announce Type: new Abstract: In recent years, graph anomaly detection (GAD) based on frequency-domain filtering have achieved promising results. However, existing approaches still f

tutorialsarxiv-cs-ai

FedCMAPSS: A Benchmark for Federated Learning in Remaining Useful Life Estimation

model-releasesarxiv-cs-lg

arXiv:2608.26433v1 Announce Type: new Abstract: Data-driven prognostics and health management has emerged as a key enabler for Industry 4.0, yet the development of robust remaining useful life (RUL) e

Federated Adversarial Training with Transformers

arXiv:2206.02131v2 Announce Type: replace-cross Abstract: Federated learning (FL) has emerged to enable global model training over distributed clients' data while preserving its privacy. However, the

researcharxiv-cs-cv

FIDA: Feature Instability-Driven Attack on Self-Supervised Facial Representation

arXiv:2608.26861v1 Announce Type: new Abstract: Self-supervised learning (SSL) models are vulnerable to backdoor attacks. However, the systemic risks they pose in face representation have received lit

applicationsarxiv-cs-cv

Finding the Right Evidence: Factor-Guided Coarse-to-Fine Reasoning for Long Videos

arXiv:2608.26355v1 Announce Type: new Abstract: While LVLMs rapidly improve, long-video question answering still remains challenging: relevant evidence is sparse, and question-relevant context often f

agentsarxiv-cs-cv

Fine-Tuning of Transformer models with Frames

arXiv:2608.26430v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) strategies such as Low-Rank Adaptation (LoRA) are effective solutions for fine-tuning large-scale pre-trained mod

FireRedAudio: A General-Purpose Audio Language Model with Decoupled Continuous Representations for Understanding and Generation

arXiv:2608.24168v2 Announce Type: replace Abstract: A unified audio model must recognize and understand linguistic, paralinguistic, and environmental information while supporting speech synthesis and