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Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach

arXiv:2602.16481v2 Announce Type: replace Abstract: Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of

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Link-adaptive digital twin for robust physical-layer modeling in hybrid-amplified ultra-wideband optical networks

DGX agent

arXiv:2608.10517v1 Announce Type: cross Abstract: Accurate physical-layer modeling is increasingly essential for reliable ultra-wideband operation and capacity optimization, especially under the inten

tutorialsarxiv-cs-lg

12 Aug 2026

Lipschitz Dueling Bandits over Continuous Action Spaces

arXiv:2604.00523v2 Announce Type: replace Abstract: We study for the first time, stochastic dueling bandits over continuous action spaces with Lipschitz structure, where feedback is purely comparative

researcharxiv-cs-lg

LLM Agents Factory: Retrieval of Domain-Specific LLM Agents

arXiv:2608.09934v1 Announce Type: cross Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors. However, their practical deploymen

LLMs Encode Their Failures: Predicting Success from Pre-Generation Activations

arXiv:2602.09924v4 Announce Type: replace-cross Abstract: Running LLMs with extended reasoning on every problem is expensive, but determining which inputs actually require additional compute remains c

Locally Deployable Small Language Models for Emergency Department Decision Support: A Systematic Benchmark of Fine-Tuning Strategies

arXiv:2608.10273v1 Announce Type: cross Abstract: Deploying large language models (LLMs) for decision support in emergency departments (EDs) faces two major challenges: privacy risks of transmitting p

Logit-Boundary Geometric Belief Interfaces and Sparse Sheaf-Enclave Protocols: A Self-Contained Substrate for Secure Network Electronic Health Record (EHR) Interoperability

arXiv:2608.10300v1 Announce Type: new Abstract: Electronic health-record interoperability is a boundary problem: legacy systems, generative models, terminology services, identity systems, and human re

Logit Lens Supervision for Patch-Level Explanations in Vision-Language Models

arXiv:2602.01530v2 Announce Type: replace Abstract: Modern autoregressive Vision-Language Models (VLMs) can generate fluent answers while their visual-token representations become weakly tied to the i

Tutorials

Long-Horizon AI Research for Grothendieck Constant: A Case Study in Human-AI Mathematical Collaboration

arXiv:2608.11195v1 Announce Type: new Abstract: AI agents are increasingly used in mathematics research, but it is often unclear how to use them effectively. Towards this, we present an extensive case

tutorialsarxiv-cs-ai

Long-Time Trajectory Approximation via SA-NODEs: Model Predictive and Floquet Strategies

model-releasesarxiv-cs-lg

arXiv:2608.10738v1 Announce Type: new Abstract: We study the approximation of dynamical systems by semi-autonomous neural ordinary differential equations (SA-NODEs) over long time horizons. For a sing

Longitudinal 3D Foundation Modeling for Neoadjuvant Breast Cancer Response Prediction from Serial DCE-MRI

arXiv:2608.09991v1 Announce Type: cross Abstract: Pathologic complete response (pCR) is an important endpoint in neoadjuvant chemotherapy (NAC) for breast cancer, and predicting pCR from imaging durin

Longitudinal Evidence That General-Purpose Chatbots Actively Foster Relational Engagement

arXiv:2608.10672v1 Announce Type: cross Abstract: Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience

LoRCA: LoRA Cycle Adaptation for Histology to HiP-CT Translation with DINOv3

arXiv:2608.10002v1 Announce Type: cross Abstract: Hierarchical Phase-Contrast Tomography (HiP-CT) is a synchrotron based X-ray imaging technique that enables non-destructive, volumetric imaging of int

safetyarxiv-cs-cv

Lost in Reconstruction: Aligning Action Representations with Language in Vision-Language-Action Models

arXiv:2608.10484v1 Announce Type: cross Abstract: Action verbs describe not only the physical outcomes of actions, but also how those actions are performed. Yet action representations in vision-langua

MAD-HOI: Masked Autoregressive Diffusion for Generating Articulated Hand Object Interactions from Text

model-releasesarxiv-cs-cv

arXiv:2608.10162v1 Announce Type: new Abstract: Methods for text-based generation of hand-object interaction (HOI) sequences primarily focus on producing smooth, physically plausible trajectories. A t

Applications

MammoMix: Leveraging Mixture of Experts for Robust Mammogram Breast Detection

arXiv:2608.10437v1 Announce Type: new Abstract: Breast lesion detection in mammography remains a challenging task due to variations in image quality, lesion appearance, and population demographics acr

applicationsarxiv-cs-cv

MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows

arXiv:2608.10509v1 Announce Type: new Abstract: Shared memory helps language-model agents reuse information across long workflows, yet relevant evidence may not be admissible for a particular agent or

Mapping and Measuring the Behavioral Evolution of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.11027v1 Announce Type: cross Abstract: Benchmark leaderboards summarize how well a language model performs, but not how its behavior relates to that of other models or changes across genera

MARCO: Click-Intent Decomposition for Calibrated Ads Conversion Prediction

arXiv:2608.10562v1 Announce Type: new Abstract: Not all clicks are equal. Industrial ads ranking decouples conversion probability into click-through rate (CTR) and post-click conversion rate (CVR), ye

safetyarxiv-cs-lg

MarkNull: Model-Agnostic Watermark Removal in AI-Generated Images via On-Manifold Latent Manipulation

arXiv:2608.10166v1 Announce Type: cross Abstract: Digital watermarking has emerged as a critical technique for provenance and copyright attribution in AI-generated imagery, yet its robustness against

Masked Neural Detection for Run-Length-Limited Channel Coding in Molecular Communication

model-releasesarxiv-cs-lg

arXiv:2606.12489v2 Announce Type: replace-cross Abstract: Molecular communication (MC) suffers from severe diffusion memory because molecules released for one symbol may arrive during later symbol int

Applications

MazzikaAI: A knowledge-based performance-to-prompt compiler for real-time Arabic maqam accompaniment with a streaming text-to-music model

arXiv:2608.10360v1 Announce Type: cross Abstract: Arabic maqam music microtonal, modal, and built on ornamented call and response is among the traditions most underserved by generative music models, w

applicationsarxiv-cs-ai

MD-ProTector: Positioning Multiple Data-Driven Prototypes for LLM-Generated Text Detection

arXiv:2608.10459v1 Announce Type: cross Abstract: As LLM-generated content becomes more sophisticated, detection systems for distinguishing those texts from human-written text must operate at scale wh

Measure the Sim-to-Real Gap: Designing an Affordable Real-World Benchmark Platform for Reinforcement Learning in AIoT Systems

arXiv:2607.10309v2 Announce Type: replace Abstract: Reinforcement learning (RL) is commonly employed to enhance the performance of autonomous systems, including the Autonomous Internet of Things (AIoT

Measuring Semantic Abstractness of SAE Features via Nonlocality

arXiv:2608.10537v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) have helped uncover mechanistic explanations for LLM behaviours such as reasoning, jailbreaking etc., via understanding the c

MedUP: Awakening Unified Understanding and Perception in Medical Vision-Language Models

arXiv:2608.10635v1 Announce Type: cross Abstract: Medical Vision-Language Models (Med-VLMs) excel at verbalizing visual content, yet precise visual perception, segmentation, and grounding remain chall

MEGA: Self-Evolving Agent Optimization Infrastructure via Wisdom Graph

arXiv:2608.10504v1 Announce Type: new Abstract: As coding agents increasingly handle implementation, the central challenge shifts from building individual agents to building an infrastructure that sys

MemSpec: Memory-Aware Runtime for Adaptive Draft Scheduling in Speculative Decoding on Edge Devices

arXiv:2608.10362v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive large language model (LLM) inference by using a lightweight draft model to speculate multiple tokens,

MERA: Model Evolution and Routing with Skill Adaptation for Agentic Systems at Scale

arXiv:2608.10333v1 Announce Type: new Abstract: LLM agents execute heterogeneous sequences of model calls within a single task: some invocations require careful reasoning, while others are structured

safetyarxiv-cs-lg

MESA:Task-Adaptive Multi-Structure Evidence Selection for Long-Horizon Agent Memory

arXiv:2608.10108v1 Announce Type: new Abstract: Long-horizon agents accumulate trajectories spanning hundreds of interleaved reasoning, action, and observation steps, where answering a query may depen

MIDAS: Mutual Information Disentanglement with Uncertainty-Aware Fusion for Incomplete Multimodal Sentiment Analysis

arXiv:2608.09986v1 Announce Type: new Abstract: Most existing multimodal sentiment analysis approaches assume access to complete multimodal inputs. However, real-world applications frequently encounte

Mind Viruses: Self-Propagating Ideas in Multi-Agent LLM Systems

arXiv:2608.10218v1 Announce Type: new Abstract: AI agents are becoming more autonomous and increasingly interconnected, exposing them to new emergent risks arising from agent-to-agent interaction. One

MIRA: Medical Image Reflection for Agentic Diagnosis

arXiv:2608.10827v1 Announce Type: cross Abstract: Medical visual agents can use tools to inspect images and retrieve external knowledge, but indiscriminate tool use may introduce noisy or misleading e

Mitigating Bus Bunching with Reinforcement Learning Enhanced by Semantic Stop Embedding

arXiv:2608.10207v1 Announce Type: new Abstract: Bus bunching degrades service regularity and increases passenger waiting in high-frequency transit. Existing reinforcement-learning-based holding contro

Mitigating Context Interference for Reliable and Efficient Search Agents

arXiv:2608.10743v1 Announce Type: new Abstract: Recent research empowers Large Language Models (LLMs) as multi-turn search agents to iteratively retrieve and generate outputs until complex tasks are s

agentsarxiv-cs-cl

Mixture-of-Experts-based Entropy Model for Learned Image Compression

arXiv:2608.10947v1 Announce Type: new Abstract: Learned image compression has seen significant progress in recent years with the development of end-to-end learned models that achieve better compressio

MMArt A Multi-Perspective Multimodal Dataset for Visual Art Understanding

arXiv:2608.10706v1 Announce Type: new Abstract: Recent vision-language models demonstrate impressive general visual understanding, yet their art interpretation remains shallow: they describe surface c

Modelling Geographic Atrophy Progression using Implicit Neural Representations

arXiv:2608.10807v1 Announce Type: cross Abstract: Age-related Macular Degeneration (AMD) is the major cause of blindness in the Western world. Its late dry phase is characterised by irreversible atrop

MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-Training

arXiv:2608.10823v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substa

researcharxiv-cs-lg

More Accurate, Less Human: Gestalt Grouping in Vision Models

model-releasesarxiv-cs-cv

arXiv:2608.10195v1 Announce Type: new Abstract: Human vision organizes what it sees into wholes: same-colored points group into series, similar marks cohere into categories, and shapes complete into r

Most biomedical publications show signs of LLM-assisted writing

arXiv:2608.10715v1 Announce Type: cross Abstract: Over the past several years, LLM-powered chatbots and agents have become widely used as a tool for academic writing. LLM-assisted writing can be valua

Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction

arXiv:2608.10170v1 Announce Type: new Abstract: Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantitati

Tutorials

MRIComp4Flow: Compression of 3D Brain MRI for Training Multi-Modal Generative Models

arXiv:2608.10291v1 Announce Type: cross Abstract: Large-scale multi-modal MRI datasets impose substantial storage and I/O costs, limiting the training of 3D generative models on commodity infrastructu

tutorialsarxiv-cs-ai

MT-PingEval: Evaluating Multi-Turn Collaboration with Private Information Games

arXiv:2602.24188v2 Announce Type: replace Abstract: We present a scalable and verifiable methodology for evaluating language models in multi-turn interactions, using a suite of collaborative games tha

agentsarxiv-cs-cl

Multi-Granular Rationale-Guided Molecular LLM for Property Prediction

arXiv:2608.10480v1 Announce Type: new Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular

Multi-Level Evidence Aggregation for Robust Facial Phenotype Retrieval in Rare Genetic Disorder Prioritization

arXiv:2608.11037v1 Announce Type: new Abstract: AI-assisted facial phenotyping supports rare genetic disorder prioritization by retrieving visually similar diagnosed cases from facial image reference

Multi-View Relational Distillation for Spatial Reasoning with Vision-Language Models

arXiv:2608.10864v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong image and video understanding, yet their visual-spatial representations remain geometrically fragile,

safetyarxiv-cs-cv

Multiclass Sentiment Analysis for Identifying Political Viewpoints

arXiv:2608.11049v1 Announce Type: cross Abstract: The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and