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arXiv:2608.22472v1 Announce Type: new Abstract: Function calling represents the core capability of agentic large language models (LLMs). Existing research has focused on enhancing LLMs function-callin

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25 Aug 2026

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Unlearning Is Not Just Erasing: Temporal Decoupling via Generation Inequality

DGX agent

arXiv:2608.23020v1 Announce Type: cross Abstract: Large language models (LLMs) require effective unlearning to address privacy regulations and safety concerns. However, achieving precise forgetting wi

local-aiarxiv-cs-ai

25 Aug 2026

When Names Cross Scripts: A Source-Grounded Benchmark for Historical Entity Reconciliation in the Mongol World

arXiv:2608.23507v1 Announce Type: cross Abstract: Historical people may appear under different languages, scripts, and transcription traditions, while distinct individuals may share highly similar or

25 Aug 2026

Your AI, On a Dial: Controlling Investment Bias in LLMs with a Single Neuron

arXiv:2608.22852v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific inve

25 Aug 2026

Aristotelian Manifolds: Leveraging Platonic Perceptual Features for Backpropagation Free Rapid Concept Learning

arXiv:2608.20682v1 Announce Type: new Abstract: This paper formalizes and systematically characterizes Aristotelian Manifolds, a generalized structural framework built upon the Platonic Representation

Building and Evaluating a Synthetic Bengali Speech Resource for Telecom Customer Care

model-releasesarxiv-cs-cl

arXiv:2608.20346v1 Announce Type: new Abstract: Speech systems used in customer-facing applications often require domain-specific language coverage. We present a synthetic Bengali speech dataset for t

Tutorials

Decoupled Vision-Language System for Multimodal Understanding and Generation

arXiv:2608.20382v1 Announce Type: new Abstract: We introduce a new architecture design for multimodal large language models (MLLMs), Libra, capable of both multimodal understanding and generation. Lib

tutorialsarxiv-cs-cl

Edge-Based Agentic Retrieval-Augmented Generation for Autonomous FHWA Bridge Inspection Compliance

arXiv:2608.20372v1 Announce Type: cross Abstract: The Federal Highway Administration (FHWA) mandates that over 600,000 bridges in the United States be evaluated against the Recording and Coding Guide

Evidence-Consistent Generative Detection under Scenario-Level Distribution Shift

arXiv:2608.21043v1 Announce Type: new Abstract: Conventional in-distribution evaluation can overestimate robustness when training and test data share recurring task-specific patterns or surface cues.

researcharxiv-cs-cl

From Regulation to Implementation: A Critical Evaluation of LLM-Assisted Regulatory Compliance in Industry

arXiv:2608.21317v1 Announce Type: new Abstract: The European Union (EU) has emerged as a leading regulatory body in the development of sustainability and privacy regulations. While new regulation requ

Fuzzy-MoE: Interpretable Regime-Conditioned Expert Routing for Non-Stationary Multivariate Time Series Forecasting

arXiv:2608.20761v1 Announce Type: cross Abstract: In non-stationary multivariate time series, different variables and samples often exhibit heterogeneous latent dynamic states, while existing deep for

Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence

arXiv:2608.21156v1 Announce Type: cross Abstract: LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms includin

Applications

Keyed Provenance Watermarking with Complementary Lattice-Based Secure Aggregation for Federated Learning

arXiv:2608.20580v1 Announce Type: cross Abstract: Federated learning (FL) is vulnerable to multi-level attacks. However, existing methods address them separately, leaving FL exposed to data leakage, u

applicationsarxiv-cs-lg

Learning Prostate Anatomy at Test Time for Cancer Detection in Micro-Ultrasound

arXiv:2608.20557v1 Announce Type: new Abstract: Domain shift across clinical centers using different imaging hardware or acquisition protocols remains a fundamental barrier to deploying deep learning

Lift, Associate, and Fuse: A Decision-Centric Framework for 2D-to-3D Foundation Model Transfer

arXiv:2608.20659v1 Announce Type: new Abstract: Methods that transfer predictions from two-dimensional foundation models into three-dimensional segmentation are commonly grouped by task or representat

One Hierarchy, Two Systems: Semantic Product IDs for Discovery-Surface Ranking and Search-Page Query Reformulation

arXiv:2608.20640v1 Announce Type: cross Abstract: Multi-merchant e-commerce catalogs contain equivalent and related products under different merchant-scoped identifiers, fragmenting behavioral evidenc

Ontology-supported AI Model and Dataset Management

arXiv:2608.21224v1 Announce Type: new Abstract: Recently, there has been a great deal of research into improving AI methods and their application. The main focus is on tracking progress, enabling tran

Poly-InstructTTS: Learning In-the-Wild Expressive Speech Synthesis from Open-Ended Instructions

arXiv:2608.20387v1 Announce Type: cross Abstract: While recent text-to-speech (TTS) models achieve high naturalness, controlling fine-grained expression via natural-language instructions remains chall

PSK at WMT 2026 MIST: Task-Specialized QLoRA Adapters for Multilingual Summarization and Question Answering

arXiv:2608.20757v1 Announce Type: cross Abstract: We describe the PSK submission to the WMT 2026 Multilingual Instruction Shared Task. Our system uses the 3.35B-parameter Tiny Aya Global model with th

Representation Affects Retrieval: A Case Study of Skill Discovery and Routing in a Multimodal Agent Harness

arXiv:2608.20389v1 Announce Type: new Abstract: A production agent harness must discover and rank, from a growing library of skills, the one most appropriate for a user's task. At small scale this sel

TRACE: Training-time Report-guided and Clinically Ordered Concept Editing

arXiv:2608.20809v1 Announce Type: cross Abstract: Breast ultrasound diagnosis relies on clinically meaningful semantic concepts, yet most deep learning methods adopt end-to-end image-to-label paradigm

Trustworthy RAG: An Evaluation Agent for Detecting Misinformation and Knowledge Poisoning in Generative AI Systems

arXiv:2608.21095v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds Large Language Model (LLM) outputs in external knowledge, but RAG systems usually trust whatever they ret

Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning

arXiv:2504.09772v3 Announce Type: replace Abstract: Test-Time Scaling has emerged as a powerful method to extend the reasoning capabilities of Large Language Models. However, single-agent TTS faces si

When Failures Propagate: Causal Failure Attribution in Agentic Retrieval-Augmented Generation

arXiv:2608.20627v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves retrieval, reasoning, and answer generation across multiple hops. A retrieval error at hop 1

Why2Speak: Faithful Reasoning for Abstaining Action Policies

arXiv:2608.20670v1 Announce Type: new Abstract: Many agentic systems must repeatedly choose between acting and abstaining, making faithful reasoning important for oversight: an explanation is useful o

Local Ai

An Agentic Approach for Active Data Collection, Travel Behavior Modeling, and Weather-Sensitive Demand Prediction

arXiv:2608.20320v1 Announce Type: new Abstract: Travel behavior research increasingly combines digital data collection with predictive modeling, yet these stages are often developed and evaluated sepa

local-aiarxiv-cs-ai

Artificial Intelligence for Workflow Analysis in Colorectal Surgery: A Multicentric, Cross-Procedural Development and Generalization Study

arXiv:2608.20154v1 Announce Type: new Abstract: Minimally invasive colorectal surgeries (MIS-CRS) are characterised by significant variability and inconsistent outcomes. ColoWorkflow, a tool for the v

Break It Down, Pass It On: Cross-Task Skill Transfer in LLM Agents

arXiv:2608.20274v1 Announce Type: new Abstract: Large language model (LLM) agents can induce skills from completed tasks and reuse them later to grow more capable with experience. In practice, induced

CacheRoute: Planned Prefix-Affinity Routing for Large-Scale LLM Serving

model-releasesarxiv-cs-lg

arXiv:2608.19677v1 Announce Type: cross Abstract: Prefix caching avoids prefill only when a repeated request returns to a server that still holds the prefix KV. Cache-blind balancing disperses that re

Compliance, Capability, and Conflict: Benchmarking Multimodal LLMs under System Messages

model-releasesarxiv-cs-cl

arXiv:2608.19207v1 Announce Type: new Abstract: Production deployments of Multimodal Large Language Models (MLLMs) increasingly rely on system messages to govern model behavior. Yet existing benchmark

Daedalus-150M: A Convolution-Attention Hybrid Designed for CPU Inference

arXiv:2608.20210v1 Announce Type: cross Abstract: Small language models are usually built like large ones and then squeezed onto a CPU afterwards. We did the opposite: we fixed the target first, one u

Decoding silent reading from non-invasive EEG

arXiv:2608.20186v1 Announce Type: new Abstract: Non-invasive decoding of inner speech faces a fundamental data problem: a corpus pairing brain activity with a person's spontaneous inner monologue cann

researcharxiv-cs-lg

Deep-MKV-TS: Path-Dependent McKean--Vlasov Control for Financial Time Series Generation

arXiv:2608.19394v1 Announce Type: cross Abstract: We introduce Deep-MKV-TS, a path-dependent McKean-Vlasov framework for financial scenario generation. The stochastic dynamics are chosen by matching s

researcharxiv-cs-lg

DiverValue-Bench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values

arXiv:2509.08022v3 Announce Type: replace-cross Abstract: Aligning large language models (LLMs) with diverse human values is essential for safe and effective deployment, yet existing benchmarks often

Tutorials

DPC-Net: Dual-Prior Collaborative Network for All-in-One Image Restoration

arXiv:2608.20141v1 Announce Type: new Abstract: All-in-One Image Restoration (AiOIR) aims to handle diverse degradations within a unified model. However, existing methods often overlook image semantic

tutorialsarxiv-cs-cv

Electronic Navigational Chart Change Classification

arXiv:2608.20218v1 Announce Type: new Abstract: Electronic Navigational Charts (ENCs) are geospatial vector datasets used in maritime navigation systems that represent hydrographic and navigational in

Tutorials

Exploiting Completeness Perception with Diffusion Transformer for Unified 3D MRI Synthesis

arXiv:2602.18400v3 Announce Type: replace-cross Abstract: Missing data problems, such as missing modalities in multi-modal brain MRI and missing slices in cardiac MRI, pose significant challenges in c

tutorialsarxiv-cs-cv

Frequency-Aware Continual Learning for Smart Contract Vulnerability Detection with Large Language Models

arXiv:2608.19680v1 Announce Type: new Abstract: Smart contract vulnerability detection with Large Language Models (LLMs) faces three causally linked challenges. First, new vulnerability categories dem

G-CARL: Grounded Checklist-Aligned Reward Learning for Patient-Oriented Medical Report Interpretation

arXiv:2608.20331v1 Announce Type: cross Abstract: Personalized interpretation of medical reports has emerged as an increasingly important need among patients. Addressing this need requires both eviden

Holtercare-Bench: A Multimodal Benchmark for Evaluating Long-Term Dynamic ECG Analysis

model-releasesarxiv-cs-lg

arXiv:2608.19297v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) excel in medical applications, most of them favor static images or short-term signals. In the critical fi

Loreley: Repository-Scale Program Evolution with Quality-Diversity Search

arXiv:2608.19703v1 Announce Type: cross Abstract: Sequential agent search accumulates changes from its current champion but discards alternative branches; independent proposals preserve breadth but re

M3: A State-Event Generative Foundation Model for Market Microstructure Dynamics

arXiv:2608.19227v1 Announce Type: cross Abstract: Market microstructure simulation aims to model how liquidity, prices, and order flow evolve in electronic financial markets. Since market data reveal

researcharxiv-cs-lg

MaliciousSkillBench: A Comprehensive Benchmark for Malicious Agent Skill Detection

arXiv:2608.19901v1 Announce Type: cross Abstract: Agent Skills extend LLM agents with reusable instruction packages that may also include scripts, resources, and service configuration. This creates a

Applications

Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

arXiv:1905.11395v2 Announce Type: replace Abstract: Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban c

applicationsarxiv-cs-lg

PACT: Phenotype-Aware Contrastive Team Representation for Multi-Phenotype Grouped Ad Hoc Teamwork

arXiv:2510.25340v2 Announce Type: replace-cross Abstract: Learning to collaborate with various unfamiliar teammates poses a great challenge in the domain of multi-agent systems. Existing ad hoc teamwo

Phantom Gains: Auditing Self-Improvement Against a Measured Null

arXiv:2608.20290v1 Announce Type: new Abstract: Whether a language model has improved itself is increasingly judged not by mean accuracy but by which individual problems it gains and loses. Tracking t

Separating Covariate Shift from Mechanism Change with Two Discriminators: CJSD, a Conditional Discrepancy with an Exact Covariate-Concept Decomposition

arXiv:2608.19885v1 Announce Type: cross Abstract: Streaming systems that maintain a pool of expert models must repeatedly decide whether to reuse an existing expert for arriving data, spawn a new one,

The Asymmetric Harms of LLM Compression

arXiv:2608.19670v1 Announce Type: new Abstract: Large language models (LLMs) compression reduces deployment costs, but standard aggregate metrics like perplexity and accuracy often mask underlying beh

safetyarxiv-cs-cl