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arXiv:2609.05113v1 Announce Type: new Abstract: Counterfactual explanations for graph-structured data seek to determine minimal and realistic modifications required in an input graph to alter a model'

tutorialsarxiv-cs-lg

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Research

A Constraint-Aware Generative Framework for Synthetic Origin-Destination Demand in Logistics Networks

DGX agent

arXiv:2609.04345v1 Announce Type: cross Abstract: Large-scale logistics networks require synthetic data generation capabilities to support scenario-based planning under novel conditions-such as networ

researcharxiv-cs-lg

7 Sept 2026

A Cost-Aware Agentic Architecture for NL-to-SQL over Nested Enterprise Schemas, with a New Benchmark

arXiv:2609.04641v1 Announce Type: new Abstract: Natural-language-to-SQL systems have ad- vanced rapidly on academic benchmarks, yet production enterprise schemas exhibit graph- like, semi-structured,

A couple years later, with GPT-6. https://underdark-duel.netlify.app Apparently the mindflayer has a '101-bone skeletal rig' (This is 5E 201…

model-releasesethan-mollick--x

A couple years later, with GPT-6. https://underdark-duel.netlify.app Apparently the mindflayer has a '101-bone skeletal rig' (This is 5E 2014 rules, and I didn't see major errors, though the mind flay

A Data Fusion Framework for Grounding Aerospace Surrogate Model via Experimental Wind-Tunnel Observations

arXiv:2609.04267v1 Announce Type: new Abstract: Aerodynamic surrogate models trained on high-fidelity CFD data reproduce numerical predictions of both scalar outputs and entire fields accurately, yet

A Deep Generative Model for Synthesizing Labeled Wireless Signals

arXiv:2609.05396v1 Announce Type: new Abstract: Wireless signals with position-related labels are pivotal for both performance evaluation and model training in the realm of wireless sensing. However,

A Differentiable Neural Surrogate for Photon Propagation in Neutrino Telescopes

arXiv:2609.04695v1 Announce Type: cross Abstract: Large-volume neutrino telescopes infer neutrino properties from Cherenkov light, but simulating the transport of billions of photons through highly sc

A Fairness Audit of the Duckworth-Lewis-Stern Method: Format-Specific and Gender-Differential Bias, with an Interpretable Calibration Layer for Cricket Target Revision

model-releasesarxiv-cs-lg

arXiv:2609.04754v1 Announce Type: new Abstract: The Duckworth-Lewis-Stern (DLS) method has been the international standard for revising target scores in rain-interrupted limited-overs cricket since 19

A few days ago, Anthropic shared this brilliant prompt. I was surprised by how it significantly improved writing with Fable 5.1. Even more s…

A few days ago, Anthropic shared this brilliant prompt. I was surprised by how it significantly improved writing with Fable 5.1. Even more surprising, it also improved writing for GPT-5.6 Sol. I have

model-releasesdair-ai--x

A Generalizable Feature Extractor for Alzheimer's-Related Brain MRI Tasks

arXiv:2609.05400v1 Announce Type: new Abstract: When there is not enough labeled data to properly train deep learning models, transfer learning can help. We still do not fully understand how effective

researcharxiv-cs-cv

A Human-in-the-Loop Framework for AI-Assisted Scoring in Large-Scale Writing Assessment

arXiv:2609.05143v1 Announce Type: cross Abstract: The integration of artificial intelligence (AI), particularly large language models (LLMs), into educational assessment has opened new opportunities t

A Hybrid Predictive Ensemble of Machine Learning and Deep Neural Networks for Early Cardiovascular Disease Risk Assessment

arXiv:2609.05146v1 Announce Type: new Abstract: This study introduces an intelligent framework that integrates machine learning and deep neural network ensemble techniques for early detection and prog

applicationsarxiv-cs-ai

Industry

A look at Anthropic's Labs team, a ~20-person group led by cofounder Ben Mann that acts as an internal startup incubator for developing flagship products (Stephen Council/Business Insider)

Stephen Council / Business Insider: A look at Anthropic's Labs team, a ~20-person group led by cofounder Ben Mann that acts as an internal startup incubator for developing flagship products — Inside A

industrytechmeme

A Quantum Variational Approach to Prototypical Recurrent Unit

arXiv:2609.04354v1 Announce Type: new Abstract: We introduce a lightweight Quantum Prototypical Recurrent Unit (QPRU) that requires significantly fewer parameters than both classical recurrent archite

Industry

A record 12.7M graduates are entering China's workforce in 2026 as AI adds uncertainty to an oversaturated job market with a shrinking pool of entry-level roles (Yan Zhuang/New York Times)

Yan Zhuang / New York Times: A record 12.7M graduates are entering China's workforce in 2026 as AI adds uncertainty to an oversaturated job market with a shrinking pool of entry-level roles — A record

industrytechmeme

A Removal Based Approach to Improve LLM Faithfulness at Test-Time

arXiv:2609.04343v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for consequential decisions, making their explanations an important tool for auditing model behavior.

A Repeated-Measurement Study for Cultural Analytics of English Song Lyrics Using Five Large Language Models

arXiv:2609.04428v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to annotate cultural texts at scales that are impractical for human coders. However, before their out

A Roadmap for MEG Foundation Models

arXiv:2609.04461v1 Announce Type: cross Abstract: Foundation models are beginning to reshape brain-signal analysis by moving the field beyond task-specific decoding pipelines toward reusable models pr

A Robust Watermark-based Fingerprint Framework for GNNs Ownership Verification

arXiv:2609.04772v1 Announce Type: new Abstract: The high training cost of Graph Neural Networks (GNNs) has raised growing concerns regarding model ownership infringement, such as model stealing and un

applicationsarxiv-cs-lg

Local Ai

A Schema Bounded Language Model for Refining Robot Policies Without Destabilizing Local Learning

arXiv:2609.05133v1 Announce Type: cross Abstract: This paper addresses navigation by composite heterogeneous robots in a decentralized system when policy reasoning and local control operate at differe

local-aiarxiv-cs-ai

A Semantic Model of Genetic Evidence: A Step Toward Bridging the Basic-Science-Clinic Gap

arXiv:2609.04509v1 Announce Type: cross Abstract: Scientific and clinical decision-making depends on evidence from the primary literature, but existing standards for representing that evidence (FHIR E

Hardware

A Sim-to-Real Study of Surface-Code Decoder Benchmarking

arXiv:2609.04557v1 Announce Type: cross Abstract: Quantum error-correction decoders are typically benchmarked against synthetic circuit-level noise, under the assumption that a decoder's ranking under

hardwarearxiv-cs-lg

A Structured Debate-Mixture-of-Agents Framework for Complex Clinical Diagnostic Decision Support

arXiv:2609.05069v1 Announce Type: cross Abstract: Large language models (LLMs) show potential for medical tasks, but their single-turn question-answer format does not reflect how clinical diagnosis is

A Systematic Comparison of Multilingual Interpretability Methods Reveals Anisotropy-Driven Failures

arXiv:2609.04819v1 Announce Type: new Abstract: Multilingual language models develop shared cross-lingual representations, and various interpretability methods claim to quantify this sharing. These me

researcharxiv-cs-cl

A Systematic Evaluation of Cross-Lingual Consistency Enhancement Methods in Multilingual Language Models

arXiv:2609.04409v1 Announce Type: cross Abstract: Multilingual language models often produce inconsistent answers to semantically equivalent questions across languages, motivating methods to improve c

A Tree-based RAG Framework for Evidence-Intensive QA via Adaptive Planning and Topology-Aware Evidence Gathering

arXiv:2609.04981v1 Announce Type: new Abstract: Recent structured RAG methods leverage tree- or graph-based reasoning structures to improve multi-hop QA. However, they face key limitations in evidence

A Unified Physics-Aware Quantum Machine Learning Framework across Power GaN HEMTs and Logic Nanowire FETs: Predicting Unseen Process Splits and Held-Out Geometry Combinations with Lower Error and Tighter Split-to-Split Variability

arXiv:2609.05251v1 Announce Type: new Abstract: We present a unified reinforcement-learning (RL) framework that discovers compact parametrized quantum circuits (PQCs) for data-scarce device modeling.

A Verifier-Guided Explainable Reasoning Framework with Gold-Anchored QLoRA, Task-Aware Mixture-of-Experts, and Group-Relative RLVR

arXiv:2609.05221v1 Announce Type: cross Abstract: Large language models (LLMs) show strong reasoning ability, but their explanations can remain inconsistent, weakly grounded, or difficult to verify. W

Agents

Abstraction Agent

arXiv:2609.04303v1 Announce Type: cross Abstract: Information abstraction, which groups strategically similar private states into a tractable number of buckets, is essential for scaling game-solving a

agentsarxiv-cs-ai

ACE: Adaptive Calibration-Free Expert Skipping for MoE-based LLMs

arXiv:2609.05228v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures provide an efficient paradigm for scaling large language models (LLMs), yet fixed top-k routing activates the sam

Achieving Asymptotic Near-Optimality Without elta-Similarity

arXiv:2609.04464v1 Announce Type: new Abstract: Sampling-based motion planning algorithms are a popular class of trajectory planning algorithm due to their speed in complex, high-dimensional environme

researcharxiv-cs-ro

Agents

Active Inference for an Intelligent Agent in Autonomous Reconnaissance Missions

arXiv:2510.17450v2 Announce Type: replace Abstract: We develop an active inference route-planning method for the autonomous control of intelligent agents. The aim is to reconnoiter a geographical area

agentsarxiv-cs-ai

Adaptation Interfaces for In-Context Tabular Foundation Models in Time-to-Event Prediction

arXiv:2609.04901v1 Announce Type: cross Abstract: Tabular foundation models (TabFMs) achieve strong performance on structured data, particularly for standard classification and regression problems. Ye

Adaptation Needs in Robotic Systems: Assessing Behavior Trees and Their Enhancement

arXiv:2609.05331v1 Announce Type: new Abstract: Robotic systems increasingly operate in dynamic, uncertain, and open-ended environments, where design-time assumptions may no longer hold, and adaptatio

researcharxiv-cs-ro

Tutorials

Adapting from Downturns: Prediction of Long-Term Conversational-Skill Development in Mental-Health Crisis Counselors

arXiv:2609.04350v1 Announce Type: cross Abstract: How do people learn to become better conversationalists? This question is especially important in the context of mental-health counseling, where conve

tutorialsarxiv-cs-ai

Adaptive Gated Deepfake Detection for Low-Resolution and Resource-Constrained Environments

model-releasesarxiv-cs-cv

arXiv:2609.05320v1 Announce Type: new Abstract: Deepfake detection models often rely on high-quality inputs, fixed inference paths, and computationally expensive architectures, limiting their use in l

Adaptive Multi-Granularity Temporal Modeling for Weakly Supervised Video Anomaly Detection

arXiv:2609.05066v1 Announce Type: cross Abstract: As the scale of video surveillance data outpaces manual annotation capacities, weakly supervised video anomaly detection (WSVAD) has emerged as a crit

applicationsarxiv-cs-ai

Local Ai

AdaptVPR: Route-Aware Hard Positive Generation for Robust Visual Place Recognition

arXiv:2609.04369v1 Announce Type: new Abstract: Visual Place Recognition (VPR) localizes a query image by retrieving database images of the same or nearby place, yet its robustness is often degraded b

local-aiarxiv-cs-cv

After over a year of my nights and weekends, the Jenny app is done!

model-releasesr-localllama

Hi all! I just wanna say that I am tired lol. Yes, it's another harness, but I spent a lot of time and effort and have forsaken my hobbies to build the Jenny (like XJ-9) app. Jenny is a free, MIT lice

AI for Computational Design Science: A Responsible Human-AI Framework and Case Study on Short-Form Video Safety Surveillance

arXiv:2609.05270v1 Announce Type: new Abstract: Artificial intelligence (AI) is transforming not only what information systems researchers design, but also how design research is conducted. Yet existi

AI-Powered CPS-Enabled Vulnerable-User-Aware Urban Transportation Digital Twin: Methods and Applications

arXiv:2501.10396v4 Announce Type: replace-cross Abstract: We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on t

AlcaTRAz - Anchored Tree-Rule Defense Against Jailbreaks

arXiv:2609.03693v1 Announce Type: cross Abstract: Large language models (LLMs) are vulnerable to jailbreak attacks that bypass safety alignment through carefully crafted prompts. Many existing defense

Alignment Under Pressure: AR-HMD Support Tools for Action Teams

arXiv:2502.17295v2 Announce Type: replace-cross Abstract: Team communication breakdowns represent a contributor to patient safety risks within action teams-defined as interdependent groups of speciali

safetyarxiv-cs-ro

Amortizing Scaling Law Construction Costs

arXiv:2609.05016v1 Announce Type: cross Abstract: Scaling laws guide the design choices for training large foundation models, but deriving them involves training an exhaustive grid over hyperparameter

Tutorials

An Analysis of Self-supervised Pre-training with Dependent Samples

arXiv:2609.05031v1 Announce Type: cross Abstract: Self-supervised learning relies on so-called data augmentations phi(x) of unlabeled datapoints x --- for example, masking random pixels in an image x

tutorialsarxiv-cs-lg

An Attention-Guided Global and Local Fusion Framework for Lesion-Focused Image Classification

model-releasesarxiv-cs-cv

arXiv:2609.04791v1 Announce Type: new Abstract: Lesion-focused image classification presents a core analytical challenge, as discriminative signals are often sparse, spatially dispersed, and easily ob

An Empirical Study into Clustering of Unseen Datasets with Self-Supervised Encoders

arXiv:2406.02465v2 Announce Type: replace-cross Abstract: Can pretrained models generalize to new datasets without any retraining? We deploy pretrained image models on datasets they were not trained f

applicationsarxiv-cs-ai

Agents

An Energy-Based Conservative-Dissipative Latent Neural Evolution Operator for Magnetization Dynamics

arXiv:2609.04530v1 Announce Type: new Abstract: We develop an energy-based reduced-order model for micromagnetic magnetization dynamics that couples a convolutional autoencoder to a structured latent

agentsarxiv-cs-lg