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Explain Less, Understand More: Data-Efficient Personalization of Reader-Dependent Jargons

arXiv:2505.16227v4 Announce Type: replace Abstract: Personalizing jargon detection and explanation is essential for making technical documents accessible to readers with diverse disciplinary backgroun

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Human DGX agent

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Explainable Neuro-Fuzzy Prediction for Trustworthy Decision-Making in Maritime

DGX agent

arXiv:2609.24358v1 Announce Type: new Abstract: Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper prop

model-releasesarxiv-cs-lg

22 Sept 2026

Explainable Predictive Condition-based Maintenance of Naval-Propulsion Systems using Fuzzy Logic

arXiv:2609.24250v1 Announce Type: new Abstract: The shipping industry has a significant impact on the global economy, emphasizing the need for operational availability and safety through the use of ef

safetyarxiv-cs-lg

Exponential Family Synthetic Controls

arXiv:2609.23970v1 Announce Type: cross Abstract: We develop exponential family synthetic controls (EFSC), a distributional version of synthetic controls for a panel of datasets. Each cell of the pane

Extracting Arguments, Not Just Classifying Them: Instruction-Tuned LLMs for Generative Component Detection

arXiv:2609.24855v1 Announce Type: cross Abstract: Argumentative component detection (ACD) is a core subtask of Argument(ation) Mining (AM) and one of its most challenging aspects, as it requires joint

Fairness Beyond Anonymization? Demographic Leakage in German LLM-Generated Resumes

arXiv:2609.22188v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into AI-assisted hiring pipelines, including automated resume generation and screening. Under t

Applications

Falling Trees: A Model Class for Interpretable Risk Prioritization

arXiv:2609.23780v1 Announce Type: new Abstract: Many real-world decisions require prioritizing high-risk cases, such as clinicians prioritizing high-risk patients before lower-risk ones. Falling rule

applicationsarxiv-cs-lg

Fast and Robust Temporal Logic Planning via ADMM-based Trajectory Optimization

arXiv:2609.23037v1 Announce Type: new Abstract: We present a fast numerical method for safe continuous-time motion planning under Temporal Logic (TL) specifications. The method generates smooth contin

safetyarxiv-cs-ro

Fast Graph Laplacian Estimation using Effective Resistance

arXiv:2609.23668v1 Announce Type: cross Abstract: Inferring network topology from noisy node observations is a central problem in graph signal processing. In this paper, we consider Laplacian-constrai

Fathom-Vaidya: Advancing Medical Reasoning with Rubric-Based Rewards

arXiv:2609.24480v1 Announce Type: cross Abstract: Deploying Large Language Models (LLMs) in healthcare requires robust performance across two complementary dimensions - diagnostic reasoning: the conve

Feasibility Distance Fields for Heterogeneous Constraints in Robot Configuration Space

arXiv:2609.24632v1 Announce Type: new Abstract: Robot manipulators are monitored by constraint-specific indicators whose units and gradient scales are not comparable, so they do not provide a common m

researcharxiv-cs-ro

FeasibleFlow: One-Step Joint Transport of Configuration Feasibility and Trajectories for End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.23488v1 Announce Type: new Abstract: End-to-end autonomous driving maps current observations directly to future trajectories, yet those trajectories must remain valid as the scene evolves.

Feature Suppression and Differential Privacy for Residential Traffic Classification: A Two-Home Federated Study

arXiv:2609.23521v1 Announce Type: new Abstract: Residential traffic classification supports service management, but learning across homes must account for heterogeneous traffic and privacy constraints

Federated Multilingual Speech-LLMs: Architecture and Aggregation Strategy Benchmarking

arXiv:2609.23825v1 Announce Type: new Abstract: We present a comprehensive benchmark of Federated Learning (FL) for multilingual Automatic Speech Recognition (ASR), evaluating four Speech-LLM architec

Local Ai

FedMust: Semi-supervised Multi-task Student-Teacher Federated Learning for Multi-organ CT Segmentation

arXiv:2609.24627v1 Announce Type: new Abstract: Multi-organ segmentation using deep learning requires large amounts of annotated patient data; however, institutions often lack sufficiently large and d

local-aiarxiv-cs-cv

Financial Language Models as Applied Artificial Intelligence Systems for News-Based Trading under Market Frictions

arXiv:2609.23703v1 Announce Type: new Abstract: Financial language models can transform unstructured firm-specific news into structured decision signals, but financial AI research lacks an integrated

Finite Topological Space Filtrations: A Topological Framework for Data Analysis

arXiv:2512.23348v3 Announce Type: replace-cross Abstract: We introduce a data-analysis framework based on filtrations of finite topological spaces. Starting from a finite metric data set, we construct

FinsSim: A Reality-Aligned Integrated Simulation Platform for Underwater Robot Learning

arXiv:2609.23943v1 Announce Type: new Abstract: Underwater robot learning relies on simulators that integrate high-fidelity hydrodynamics, convenient learning interfaces, and a credible transition to

researcharxiv-cs-ro

Tutorials

FIRM-WM: State-factorized factual-interventional recurrent modeling for reward-free visual planning

arXiv:2609.22816v1 Announce Type: new Abstract: Reward-free latent world models can learn from offline videos and solve new image--goal tasks by optimizing actions through predicted latent futures. Th

tutorialsarxiv-cs-lg

FLARE: A Full-Lifecycle Dense Supervision Paradigm for Long-Horizon Coding Agents via Generative Reward Model

arXiv:2609.23808v1 Announce Type: new Abstract: While test-time scaling enhances Large Language Model (LLM) agents in long-horizon software engineering (SWE), sparse binary rewards (Pass/Fail) create

Hardware

FlashBoB: I/O-Efficient Exact Backward-over-Backward for Softmax Attention

arXiv:2609.24089v1 Announce Type: new Abstract: Transformer models built on the attention mechanism have become a central building block in modern deep learning, yet softmax attention remains a major

hardwarearxiv-cs-lg

FlockDiffusion: Assignment-Conditioned Diffusion for Multi-Drone Task Allocation and Completion

model-releasesarxiv-cs-ro

arXiv:2609.23745v1 Announce Type: new Abstract: Autonomous multi-drone navigation requires fleets to service distributed objectives in cluttered environments under tight computational budgets. Efficie

FoldQuantVLA: Native Low-Bit Quantization of Vision-Language-Action Models via Consistent Folding

arXiv:2609.24433v1 Announce Type: new Abstract: Low-bit vision-language-action inference must reduce observation-to-action latency while preserving robot behavior. We present FoldQuantVLA, a post-trai

safetyarxiv-cs-ro

Agents

ForceRFT: Refining VLA Actions through Force-Guided Residual Reinforcement Learning

arXiv:2609.22840v1 Announce Type: new Abstract: Force-conditioned vision-language-action (VLA) policies can respond to contact, but when trained solely on demonstrations, their recovery behavior may b

agentsarxiv-cs-ro

Forecasting Intrathecal Tracer Enhancement from Pre-Contrast Brain MRI: Direct Regression versus Flow Matching

arXiv:2609.22377v1 Announce Type: cross Abstract: Intrathecal contrast-enhanced MRI tracks how a cerebrospinal-fluid tracer spreads through the brain, but requires repeated scans over 24--48,h. Foreca

researcharxiv-cs-cv

Fractal basin geometry and the limits to predictability and reproducibility in deep learning

model-releasesarxiv-cs-lg

arXiv:2510.05606v2 Announce Type: replace Abstract: Fundamental limits to predictability are central to our understanding of many physical and computational systems. In deep learning, training outcome

Agents

FRAMES: Failure Recovery And Monitoring of Embodied Skills for Humanoid Loco-Manipulation

arXiv:2609.22538v1 Announce Type: new Abstract: Large language model (LLM) planners can decompose natural-language instructions and select reusable robot skills, but choosing the correct skill does no

agentsarxiv-cs-ro

From Articles to Publishers: Aggregating Language Model Predictions for News Source Reliability Inference

arXiv:2609.24219v1 Announce Type: new Abstract: Traditionally, the reliability of news publishers is assessed by expert organisations that evaluate editorial practices, transparency and factual standa

From Concept Alignment to Causal Grounding: An Intervention Test of Chain-of-Thought Faithfulness

arXiv:2609.23065v1 Announce Type: new Abstract: Chain-of-thought (CoT) can sound plausible yet be unfaithful to the model's underlying reasoning. Most prior work probes CoT faithfulness through input-

Tutorials

From Content Generation to Learning Support: Pedagogy-Guided Generative Video Tutors for STEM Learning

arXiv:2609.24083v1 Announce Type: new Abstract: Generative AI enables scalable production of educational videos, but current systems largely focus on producing visually coherent content rather than su

tutorialsarxiv-cs-cl

From Documented Strengths to Force Limits: Material-Informed Robotic Insertion for Construction Assembly

model-releasesarxiv-cs-ro

arXiv:2609.22609v1 Announce Type: new Abstract: Insertion is a fundamental operation in robotic construction assembly, where variations in material properties and assembly conditions make it difficult

From Latent Biomarkers to Clinical Rules: Embedding-Guided Rule Mining and Attribution-Based Translation for Interpretable Tabular Learning

arXiv:2609.22155v1 Announce Type: new Abstract: Clinical decision support tools are most useful when accurate predictions are accompanied by understandable explanations. Rule-based models provide tran

From Noise to Signal: When Outliers Seed New Topics

arXiv:2603.18358v2 Announce Type: replace Abstract: Outliers in dynamic topic modeling are typically treated as noise, yet we show that some can serve as early signals of emerging topics. We introduce

From Outliers to Topics in Language Models: Anticipating Trends in News Corpora

arXiv:2509.22030v2 Announce Type: replace Abstract: This paper examines how outliers, often dismissed as noise in topic modeling, can act as weak signals of emerging topics in dynamic news corpora. Us

From Regional to Global: Transfer Learning for Atmospheric Transport Emulators

arXiv:2609.23838v1 Announce Type: new Abstract: Greenhouse gas emissions estimates can be derived using inverse methods by combining atmospheric concentration observations with chemical transport mode

Agents

From Semantic Decisions to Feasible Trajectories: Self-Evolving LLM-Guided Optimal Control for Narrow-Space Parking

arXiv:2609.24631v1 Announce Type: new Abstract: Autonomous parking in nonconvex and narrow environments remains challenging. Although optimal-control methods can explicitly enforce vehicle dynamics an

agentsarxiv-cs-ro

From Tables to Quantified Statements: Evaluating LLM Inference Generation through Executable Verification

arXiv:2609.23966v1 Announce Type: new Abstract: LLMs can generate fluent descriptions from tables, but their outputs may remain logically unsupported by the structured data. We introduce STAT-TO-TEXT,

From Trait Vectors to Circuits: Tracing Refusal and Sycophancy Through Language Models

arXiv:2609.22224v1 Announce Type: new Abstract: A direction in activation space that changes safety-relevant behavior when steered is not necessarily one the model uses to produce that behavior on its

From UNDRR Reports to Event Records: Schema-Constrained LLM Extraction of Georeferenced Disasters

arXiv:2609.23853v1 Announce Type: new Abstract: Disaster-risk-reduction archives describe hazard events in prose that databases such as EM-DAT (Delforge et al., 2025) cannot ingest directly. We presen

Functional Emotion Without Character: Large Language Models, Aristotelian Disposition, and the Limits of Behavioral Alignment

arXiv:2609.22362v1 Announce Type: new Abstract: Debates about whether artificial systems can feel are often forced between two unsatisfactory positions: behavioral equivalence is treated as sufficient

G-NAC: Graph Neural Automata Clustering via Emergent Domain Formation

model-releasesarxiv-cs-lg

arXiv:2609.24823v1 Announce Type: new Abstract: We introduce Graph Neural Automata Clustering (G-NAC), an unsupervised clustering method in which observations interact as cells on a fixed neighborhood

Hardware

G6D: Geometric Learning-Free RGB-D 6D Pose Solver for Robotic Manipulation

arXiv:2609.23566v1 Announce Type: new Abstract: 6D object pose estimation is fundamental to robotic manipulation and automation. Recent zero-shot methods have significantly improved generalization to

hardwarearxiv-cs-cv

GAE: Learning a Geometry-Native Latent Space for 3D-Consistent World Generation

arXiv:2609.24981v1 Announce Type: new Abstract: We present a compact geometry-native latent space as a shared foundation for perception and generation. Visual generators can produce photorealistic fra

researcharxiv-cs-cv

GameHorizon Suite: Multi-Horizon Data and Evaluation in Gameplay

model-releasesarxiv-cs-cv

arXiv:2609.25001v1 Announce Type: new Abstract: Modern video games provide a measurable testbed for AI models, combining abilities of visual understanding, instruction decomposition, goal planning, an

GameReplica: A Benchmark for Black-Box Visual Game Replication by Vision-Language Agents

model-releasesarxiv-cs-cv

arXiv:2609.22308v1 Announce Type: new Abstract: Coding-agent benchmarks usually evaluate implementation after the target behavior has been specified in text, code, or demonstrations. Existing research

GAPS: Generative Active Pseudo-view Selection for Sparse-View 3D Gaussian Splatting

arXiv:2609.23436v1 Announce Type: new Abstract: Novel view synthesis from sparse observations is severely under-constrained. Although 3D Gaussian Splatting (3DGS) enables real-time rendering, it produ

researcharxiv-cs-cv

Garbage Attention in Large Language Models: BOS Sink Heads and Sink-aware Pruning

arXiv:2601.06787v2 Announce Type: replace Abstract: Large Language Models (LLMs) are known to contain significant redundancy, yet a systematic explanation for why certain components, particularly in h

Applications

GARO: Geometry-Aware Redundancy Optimization for Real-Time and High-Fidelity Dynamic Gaussian Splatting

arXiv:2609.23509v1 Announce Type: new Abstract: Novel view synthesis is a key task for dynamic scene reconstruction, where high rendering speed is essential for applications such as virtual reality. E

applicationsarxiv-cs-cv