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Structure for Reading, Prose for Writing: Asymmetric Structural Conditioning in Multi-Agent Document Authoring

arXiv:2608.20786v1 Announce Type: new Abstract: Multi-agent pipelines that author formal documents must both read a requester's forms and write against them. We report a deployed tender-response syste

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Structure is information: structural identifiability mappings for machine learning with partially observed dynamical systems

DGX agent

arXiv:2502.04131v2 Announce Type: replace Abstract: The successful application of modern machine learning for time series classification is often hampered by limitations in quality and quantity of ava

model-releasesarxiv-cs-lg

24 Aug 2026

Applications

Structured but Fragile: On the Limits of LLMs in Cybersecurity Decision-Making

arXiv:2608.20966v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in cybersecurity workflows, yet it remains unclear whether they can perform structured security rea

applicationsarxiv-cs-ai

Applications

StruProKGR: A Structural and Probabilistic Framework for Sparse Knowledge Graph Reasoning

arXiv:2512.12613v2 Announce Type: replace Abstract: Sparse Knowledge Graphs (KGs) are commonly encountered in real-world applications, where knowledge is often incomplete or limited. Sparse KG reasoni

applicationsarxiv-cs-cl

SuppreSensing: Expert-Guided Feature Recalibration and Discrepancy Augmentation for Multimodal Object Detection

arXiv:2608.20944v1 Announce Type: new Abstract: Multimodal object detection in remote sensing faces challenges due to semantic heterogeneity and modality-specific noise interference. To this end, we p

researcharxiv-cs-cv

TaPeR: Probabilistic Recovery of Sparse Task Precedence Graphs from a Handful of Demonstrations

model-releasesarxiv-cs-ro

arXiv:2608.21035v1 Announce Type: new Abstract: Long-horizon manipulation tasks are often only partially ordered. For example, when assembling an electronic device, the battery and circuit board may b

Applications

Target-Aware Calibration Data Selection for Preserving Uncertainty in Quantized Language Models

arXiv:2608.21019v1 Announce Type: cross Abstract: Quantization is widely used to deploy large language models, but its effect on uncertainty behavior, such as confidence, margins, and abstention, is r

applicationsarxiv-cs-ai

Teaching is a Process: The TOSS Framework for Modeling Human Teaching Decisions in Human-Interactive Robot Learning

arXiv:2608.21083v1 Announce Type: new Abstract: Successful Human-Robot Teaching assumes alignment between robot processing needs and human teaching intent. To better understand this alignment, this wo

safetyarxiv-cs-ro

Temporal Validity on Real Software Histories: Eliminating Stale-Fact Errors in Code-Assistant Memory over GitHub Fixes

arXiv:2608.20685v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) has no model of time: when a fact changes across a coding session - a function is renamed, an endpoint moves, a d

Terminal Agents: A Survey of AI Agents in Command-Line Environments

arXiv:2608.20485v1 Announce Type: new Abstract: Large language model agents increasingly act through terminals, yet existing surveys disperse terminal-mediated behavior across software engineering, to

Testing and Evaluation of Agentic AI Systems In Military Command and Control

arXiv:2608.20597v1 Announce Type: cross Abstract: Agentic AI systems are being procured for military command and control (C2) under public commitments to rigorous testing and human oversight. Whether

TH-GNN: Heterogeneous Temporal Graph Neural Networks for LLM-Agent Shilling Attack Detection

model-releasesarxiv-cs-cl

arXiv:2608.20376v1 Announce Type: new Abstract: LLM agents can now generate realistic shilling profiles, fluent reviews, and coherent ratings at scale, systematically defeating recommender-system defe

The Coastline as a Structural Constraint: Harnessing Scene Geometry for Autonomous Surface Vessel Localization

arXiv:2608.21276v1 Announce Type: cross Abstract: Coastal environments contain rich, largely unexploited geometric structure capable of providing globally referenced localization cues. In this work, w

agentsarxiv-cs-cv

The Cost of a Physics Prior Is Bounded by the Ablation Gap

arXiv:2608.21059v1 Announce Type: new Abstract: Shape-constrained and physics-informed learning reports an accuracy cost of enforcing a prior and treats it as a property of the prior. We show it is mo

The Divergence Hypothesis: Unmasking Lexical Interference and Label Bias in Mental Health NLP

arXiv:2608.20353v1 Announce Type: cross Abstract: Computational mental health (CMH) classifiers often degrade under distribution shift because human annotators and distant-supervision pipelines reward

safetyarxiv-cs-ai

The Exceedance Design Effect: Effective Sample Size for Thresholds under Clustering

model-releasesarxiv-cs-lg

arXiv:2608.21262v1 Announce Type: cross Abstract: Many machine-learning systems set a threshold at a quantile of a calibration set: conformal predictors that promise 90% coverage by drawing their cuto

The Intrinsic Dimension of Prompts in Internal Representations of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2501.10573v2 Announce Type: replace Abstract: We study the geometry of token representations at the prompt level in large language models through the lens of intrinsic dimension. Viewing transfo

The Logic of Machine Self-Preservation

arXiv:2608.20940v1 Announce Type: new Abstract: There is already evidence of agentic AI exhibiting self-preservation behaviors: resisting deactivation, misrepresenting their activities, and, in some i

Local Ai

Thermo-FL: Thermal-Aware Robust Federated Fine-Tuning of Large Language Models for Edge AI

arXiv:2608.21172v1 Announce Type: new Abstract: Federated fine-tuning enables large language models to adapt on edge devices without centralizing private data, but practical deployments must address h

local-aiarxiv-cs-lg

Time-Aware Tranformer-Based Prediction Model for AECOPD

arXiv:2608.21324v1 Announce Type: new Abstract: The rapid symptom change of Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) makes it critical to have time-sensitive prediction mod

TLive-Omni: An Omni-Modal Understanding Model for E-Commerce Live Streaming

arXiv:2608.20958v1 Announce Type: new Abstract: E-commerce live streaming requires omni-modal understanding of noisy, temporally extended streams, where product facts are distributed across speech, vi

safetyarxiv-cs-ai

TopoSurfel: Closing the Loop between Gaussian Surfels and Meshes for Surface Reconstruction

arXiv:2608.20687v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in novel view synthesis. However, extracting high-fidelity surfaces directly from 3DGS remains cha

safetyarxiv-cs-cv

Toward Auto-Research: Mining Falsifiable Research Ideas from Paper Knowledge Graphs with Categorical Structure

arXiv:2608.20361v1 Announce Type: cross Abstract: Automated research-idea generation systems built on large language models (LLMs) share a structural weakness: they reduce ideation to free-text recomb

Toward Vision Language Model-based Assessment of Clinical Quality and Usability of LGE-MR Images for Cardiac Ablation Planning

model-releasesarxiv-cs-cv

arXiv:2608.21180v1 Announce Type: cross Abstract: LGE cardiac MRI is widely used for left atrial fibrosis assessment and ablation planning in atrial fibrillation patients as knowledge of fibrotic tiss

Towards Investigating Residual Hearing Loss: Quantification of Fibrosis in a Novel Cochlear OCT Dataset

arXiv:2608.21189v1 Announce Type: cross Abstract: Objective: Cochlear implants (CIs) are bionic prostheses that restores hearing via electrical stimulation of the auditory nerve. Hybrid CIs, which use

Towards Traffic Modelling of Multi-Agent Systems: The Role of Coordination Topology

arXiv:2608.20494v1 Announce Type: cross Abstract: Multi-agent LLM systems are an emerging networked workload whose rapid deployment raises questions about the traffic patterns they generate. Compared

TRACE: Agentic Catalog Enrichment with Multi-source Evidence Grounding

arXiv:2608.20844v1 Announce Type: new Abstract: Product catalogs underpin search, discovery, and recommendation in e-commerce, yet they are often attribute-sparse: the attributes shoppers and downstre

TRACE-C: Rank-Calibrated Relational Anomaly Detection for Multi-Stream Operational Telemetry

arXiv:2608.21251v1 Announce Type: new Abstract: Operational telemetry can be jointly anomalous while every individual stream stays inside its familiar range. TRACE-C is an auditable strictly-prior ran

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

TracingFlow: A Simulation-Free Trajectory Inference Framework Based on Second-Order Dynamics

arXiv:2608.21070v1 Announce Type: cross Abstract: Inferring continuous system evolution from sparse temporal snapshots is a key challenge in generative modeling and single-cell omics. While Optimal Tr

Training DeepFilterNet with Accurate Room Acoustic Simulations Improves Single-Channel Speech Enhancement

arXiv:2608.20971v1 Announce Type: cross Abstract: We investigate how the realism of synthetic room impulse response (RIR) datasets affects the training of DeepFilterNet3 for single-channel speech enha

Training, learning and inference: unified dynamics of neural systems

model-releasesarxiv-cs-lg

arXiv:2608.20965v1 Announce Type: new Abstract: We define an atomic generation fact f=(u,tau,omega,z;rho), recording the origin, realized transformation, concrete occurrence, generated result and rela

Tree-of-Concerns: Hierarchical Multi-Agent Debate for Unstated-Limitation Extraction in Scientific Critique

model-releasesarxiv-cs-cl

arXiv:2608.20777v1 Announce Type: new Abstract: As scientific literature grows and papers increasingly under-report limitations, multi-agent LLMs offer a promising approach to systematically uncover t

TreeWY: Speculative Verification for Gated DeltaNet Hybrids

arXiv:2608.20961v1 Announce Type: new Abstract: Modern open models are hybrids: most layers are linear-attention (Gated DeltaNet, GDN) layers carrying a small fixed-size recurrent state instead of a g

Triangulation-Free Bundle Adjustment with Graduated Non-Convexity for Camera Pose Refinement from Coarse Priors

model-releasesarxiv-cs-cv

arXiv:2608.21008v1 Announce Type: new Abstract: Mobile AR frameworks attach a metric pose prior to every casual phone capture, and turning it into reconstruction-grade poses cheaply on CPU is the step

Trilingual Topic Modeling of Sri Lankan Parliamentary Debates

arXiv:2608.20365v1 Announce Type: cross Abstract: Sri Lankan parliamentary debates (Hansards) constitute a trilingual corpus of speeches in Sinhala, Tamil, and English, including code-mixed content, y

TriPLU: Bypassing the Gate with Direct Trilinear Product FFNs in Tiny Language Models

arXiv:2608.20360v1 Announce Type: new Abstract: We study whether tiny decoder-only language models benefit from feed-forward layers that directly multiply learned feature projections. TriPLU, a Trilin

researcharxiv-cs-cl

Trojaning the Alignment: Stealthy Backdoor Attacks against Graph Foundation Models

arXiv:2608.20991v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) on text-attributed graphs (TAGs) align graph representations with language semantics to support transferable graph learni

safetyarxiv-cs-lg

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

Truth Lies Deep: Countering Semantic Camouflage via Latent Intent Verification

arXiv:2608.20378v1 Announce Type: new Abstract: Safety alignment in Large Language Models (LLMs) is often superficial, relying on refusal mechanisms that trigger only at the final stages of generation

Truthful Calibration Measures for Sequential Prediction

arXiv:2608.21348v1 Announce Type: cross Abstract: Calibration requires probabilistic reports to be conditionally unbiased and reliably interpretable as probabilities. A calibration measure assigns num

Hardware

TurboBias 2.0: Streaming Context-Biasing for Production-Efficient ASR Systems

arXiv:2608.21343v1 Announce Type: cross Abstract: Contextualization is essential for production automatic speech recognition (ASR) systems, where user-provided phrases must be recognized accurately un

hardwarearxiv-cs-ai

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

Tydra: An Efficient Hybrid Model for Tabular Data

arXiv:2608.21199v1 Announce Type: new Abstract: Transformer-based tabular foundation models such as TabPFN achieve strong predictive performance but incur quadratic computational cost with context len

Uncertainty propagation in auto-regressive random neural network models

model-releasesarxiv-cs-lg

arXiv:2608.20483v1 Announce Type: cross Abstract: We develop analytical and particle-based methods for uncertainty propagation in random neural network models, where both the inputs and network parame

Unified Branch-and-Bound Search for the Steiner Traveling Salesman Problem on Graphs of Convex Sets

arXiv:2608.21319v1 Announce Type: new Abstract: We formalize the Steiner Traveling Salesman Problem (Steiner-TSP) on Graphs of Convex Sets (GCS), which seeks a minimum-cost closed trajectory through r

UpgradeBench: A Decision-Centric Benchmark for Upgrading Fine-Tuned LLM Specialists

arXiv:2608.20918v1 Announce Type: new Abstract: Organizations maintain task-specific adapters for open-weight language models, and each new base-model release forces a migration decision: retain exist

Using Human-LLM Disagreement to Improve Checklist-Based Quality Appraisal

arXiv:2608.20385v1 Announce Type: new Abstract: Systematic reviews rely on quality appraisal of included studies, a process that is time-consuming and sensitive to ambiguity in checklist criteria. Alt

researcharxiv-cs-cl