Search: “governance”

A Cone-Constrained Bilinear Decomposition for Total Scaled-Gradient Variation Models

model-releasesarxiv-cs-cv

arXiv:2609.00036v1 Announce Type: new Abstract: The total scaled-gradient variation (TSGV) regularizer, derived from sparse modeling of piecewise-linear structures, has been shown to preserve edges an

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A Lagrangian View of Flow Matching

DGX agent

arXiv:2609.00198v1 Announce Type: new Abstract: Modern explicit-time generative models, such as Flow Matching [Lipman et al., 2023] and Rectified Flow [Liu et al., 2023], are typically derived top-dow

researcharxiv-cs-cv

2 Sept 2026

A Unified Mechanistic Analysis of Knowledge- and Safety-Based Refusals

arXiv:2609.00760v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly trained to decline queries that fall outside their knowledge (knowledge-based refusal, KR) or violate safe

safetyarxiv-cs-cl

Accelerating Chemical Kinetics for Exoplanet Atmospheres using Neural Networks

arXiv:2609.00428v1 Announce Type: cross Abstract: Observations increasingly reveal the coupled radiative, chemical, and dynamical processes that shape exoplanet atmospheres. Interpreting these atmosph

Agents

Agentic Empirical Asset Pricing: Methodological Foundations

arXiv:2609.00731v1 Announce Type: new Abstract: Recent advances in LLM agents enable a new paradigm for asset pricing, which we call Agentic Empirical Asset Pricing (AEAP): systems that autonomously c

agentsarxiv-cs-ai

AI Morbidity and Mortality: A Framework for Clinical AI Failure Review

arXiv:2609.00076v1 Announce Type: new Abstract: Clinical artificial intelligence is increasingly embedded in real-world care, yet existing safety mechanisms are poorly suited to reconstructing and lea

Analog-DB: An Agent-First Analog Integrated Circuit Database, From Blocks to Systems

arXiv:2609.01286v1 Announce Type: new Abstract: Sharing analog integrated circuit designs remains difficult: foundry non-disclosure agreements restrict the process details a design depends on, and the

Breaking the Structural Identity: Personalized Federated LoRA Fine-tuning under Rank Heterogeneity

arXiv:2609.00632v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable success across diverse domains, but their adaptation to privacy-sensitive, distributed datasets

researcharxiv-cs-ai

Ctrl-F-Resist. Practices, Challenges, and Technical Needs of Civil Society Organizations Monitoring the Far-Right Online

arXiv:2609.00808v1 Announce Type: cross Abstract: As far-right actors increasingly exploit online platforms to disseminate ideology and mobilize supporters, civil society organizations (CSOs) play a v

DeSyR: A Decoupled Symbolic Recovery Framework with PINN-Guided Structure Search and Physics-Informed Coefficient Refinement

arXiv:2609.00530v1 Announce Type: new Abstract: Recovering compact explicit solutions from neural approximations is challenging when imperfect teacher data guide symbolic topology search and coefficie

DramaChain Bench: An End-to-End Benchmark for Short-Drama Generation

arXiv:2609.00646v1 Announce Type: new Abstract: Commercial short-drama production follows a multi-stage chain: script, storyboard, keyframe imagery, shot-level video, and the finished short drama. Mos

Local Ai

Federated Trust for Embodied Robot Capability Marketplaces

arXiv:2609.00404v1 Announce Type: cross Abstract: Robot capability marketplaces, the 'app store for robot skills,' are emerging as the deployment vector for LLM-driven robot fleets. The default cloud-

local-aiarxiv-cs-ro

Generalization Bounds for Markov Algorithms through Entropy Flow Computations

arXiv:2502.07584v3 Announce Type: replace-cross Abstract: Many learning algorithms can be represented as Markov processes, and understanding their generalization error is a central topic in learning t

GeoGR^2:Zero-Shot Geospatial Inference via Geostatistically-Guided Iterative Refinement with LLMs

arXiv:2508.04080v2 Announce Type: replace Abstract: Standard large language model prompting treats geospatial inference as independent, instance-wise prediction, ignoring the fundamental spatial depen

GlossoGen: Emergent Language in Complex Multi-Agent LLM Interactions

arXiv:2609.01491v1 Announce Type: cross Abstract: The growing rate at which LLM agents interact with one another raises key questions about language evolution in multi-LLM-agent settings, with implica

Human-AI Co-Interpretation for Responsible AI: A Hermeneutic Perspective

arXiv:2609.00334v1 Announce Type: new Abstract: Across law, education, policy analysis, and public moral argumentation, LLM outputs are being used often for work that requires interpretations to be ju

Jailbreaking Text-to-Image Models Through Cracks: Navigating Heterogeneous Safety Filters via Multi-Agent Debate

arXiv:2609.01168v1 Announce Type: new Abstract: Text-to-image (T2I) models remain vulnerable to jailbreak attacks that elicit Not-Safe-For-Work (NSFW) content, despite increasingly being guarded by he

Mechanism Design for Alignment and Control

arXiv:2609.01595v1 Announce Type: cross Abstract: We develop a framework for mechanism design with AI agents whose alignment (preferences) and capabilities (feasible actions and information) are unkno

On the Reliability of Generative Augmentation: A Wasserstein-Based Theoretical and Empirical Study

arXiv:2609.01410v1 Announce Type: cross Abstract: Generative data augmentation is widely used to mitigate class imbalance, yet its theoretical effect on downstream generalization remains poorly unders

Predicting Subsurface Abnormalities Growth using Physics-Informed Neural Networks

arXiv:2609.01417v1 Announce Type: new Abstract: The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data pred

Applications

Removable and Irreducible: A Token-Cost Ledger for the Multilingual Tokenization Tax

arXiv:2609.00378v1 Announce Type: new Abstract: Large language models pay a well-documented tax on non-English text: the same content costs several times more tokens, and because attention is quadrati

applicationsarxiv-cs-cl

Agents

Runtime-Independent Persistent Agents: Preserving Identity, Memory, and Code Across Models, Harnesses, and Servers

arXiv:2609.00546v1 Announce Type: cross Abstract: Agent systems are commonly described by the model and harness that currently produce their behavior. That boundary is useful for one execution but und

agentsarxiv-cs-ai

Sources of Truth: A Multi-Platform, Multilingual Audit of Citations in AI Mental Health Information Queries

arXiv:2609.00319v1 Announce Type: cross Abstract: Online health information seeking is shifting from keyword search, where users consider a ranked list of links, to conversational systems that compose

researcharxiv-cs-cl

Local Ai

Towards AI-Assisted Clinical Trial Matching: Practical Considerations, Multicenter Evaluation, and Real-World Deployment

arXiv:2609.01202v1 Announce Type: cross Abstract: Clinical trials are essential for advancing cancer care and drug development, but many fail because of insufficient patient enrollment. While there is

local-aiarxiv-cs-ai

When Compression Helps and When It Hurts: Condition-Aware Analysis of Chain-of-Thought Distillation

arXiv:2606.21704v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) distillation transfers multi-step reasoning from large reasoning models to smaller students, but verbose teacher traces infla

researcharxiv-cs-cl

A Causal Model for Locating and Unlocking Sandbagging in Model Organisms

arXiv:2608.29461v1 Announce Type: new Abstract: Sandbagging models strategically underperform on evaluations while retaining the capabilities being measured. The evaluations that guide frontier-model

Applications of Risk Science to AI Fairness Evaluation: Principles, Challenges, and Best Practices

arXiv:2608.29478v1 Announce Type: cross Abstract: Scholarly work which aims to describe potential societal impacts (e.g., risks) of proliferating technology (especially related to artificial intellige

Autoencoders in Function Space

arXiv:2408.01362v4 Announce Type: replace-cross Abstract: Autoencoders have found widespread application in both their original deterministic form and in their variational formulation (VAEs). In scien

CAST: Critique-Aware Supervision for Training Reliable Long-Horizon Tool-Calling Agents

arXiv:2608.30147v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in long-horizon, interactive, and stateful environments. In these settings, a single wrong a

safetyarxiv-cs-cl

Evaluating Perspectival Biases in Cross-Modal Retrieval

model-releasesarxiv-cs-cl

arXiv:2510.26861v4 Announce Type: replace-cross Abstract: Multimodal retrieval systems are expected to operate in a semantic space, agnostic to the language or cultural origin of the query. In practic

Facts Without Rules: Boundary Metadata Collapse in Multi-Agent LLM Handoffs

arXiv:2608.29028v1 Announce Type: new Abstract: Multi-agent LLM systems often coordinate by compressing an upstream interaction into a handoff artifact that downstream agents treat as shared state. We

Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps

arXiv:2608.29615v1 Announce Type: cross Abstract: Across industries, machine-learning systems support applications ranging from prediction and anomaly detection to forecasting, optimization, and sched

Imag-Eval: a language-grounded framework for interpretable Text-to-Image instruction following evaluation

arXiv:2608.29210v1 Announce Type: new Abstract: Text-to-Image (T2I) models have recently achieved impressive visual fidelity, yet their evaluation remains constrained by benchmarks that are often diff

Jigsaw-CRL: Recovering Global Latent Causal Order from Fragmented Multi-Client Interventions

arXiv:2608.28991v1 Announce Type: cross Abstract: Causal representation learning (CRL) aims to recover latent causal variables and their structural relations from high-dimensional observations. Existi

Learning Representations through Token Prediction: Geometry, Approximation, and Downstream Guarantees

arXiv:2608.30072v1 Announce Type: cross Abstract: Token prediction is a central pre-training objective for modern language models. Despite its empirical success, why token prediction learns broadly us

Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions

arXiv:2608.31028v1 Announce Type: cross Abstract: Scientific discovery often requires reasoning over competing hypotheses that are consistent with experimental observations. For mixed-variable and com

LLM Post-Training as Brownfield Maintenance: An Industrial Perspective on Dataware Engineering

arXiv:2608.31102v1 Announce Type: cross Abstract: Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improvements under fixed compute and mixtu

Mamba-Assisted Non-Markovian Closure for Reduced-Order Modeling

arXiv:2606.05371v2 Announce Type: replace Abstract: Reduced-order modeling of high-dimensional dynamical systems is often hindered by closure effects arising from unresolved variables, which can intro

Measuring Memory and Generalization as Separable Geometric Channels: The Topo^2 Framework

arXiv:2608.30487v1 Announce Type: cross Abstract: Deep networks trained on noisy labels simultaneously generalize on clean data and memorize flipped labels. These are usually conflated as pressures on

researcharxiv-cs-ai

Normalized Low-Rank Adaptation

arXiv:2608.31036v1 Announce Type: new Abstract: While low-rank adaptation (LoRA) is widely used for parameter-efficient model adaptation, how to regularize its training dynamics for stable and effecti

Paper Pilot: A Human-in-the-Loop Expert System for Evidence-Traceable Scientific Manuscript Generation in Applied Sciences

arXiv:2608.28596v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly embedded in scientific workflows for literature analysis, drafting, and review. Existing systems adva

Reference-Grafting Matches Fine-Tuning at Eliciting Sandbagged Capabilities

arXiv:2608.29458v1 Announce Type: cross Abstract: Sandbagging, in which a model deliberately underperforms on an evaluation despite retaining the underlying capability, threatens the safety evaluation

Responsible Integration of AI in Cancer Genomics: Barriers, Risks, and Pathways to Trustworthy Clinical Translation

arXiv:2608.30912v1 Announce Type: new Abstract: Artificial intelligence (AI) and natural language processing (NLP) are increasingly used to extract, integrate, and interpret biomedical knowledge relev

Taking the Whys Seriously: Limitations of Counterfactual Explanations in Justification and Recourse

arXiv:2608.30956v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) are widely used in explainable artificial intelligence (AI) to show how a model's outputs would change if the input

researcharxiv-cs-ai

Applications

The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning

arXiv:2511.21799v2 Announce Type: replace Abstract: Real-world machine learning (ML) pipelines rarely produce a single model; instead, they produce a Rashomon set of many near-optimal ones. We show th

applicationsarxiv-cs-lg

The Value of Depth in Message Passing on Sparse Graphs: A Kesten-Stigum Dichotomy

arXiv:2607.16676v2 Announce Type: replace-cross Abstract: How deep does a graph neural network need to be on a sparse graph? We study its purest statistical form: node classification on the sparse con

TrainSDC: Characterizing and Mitigating Silent Data Corruption in Large Language Model Training

arXiv:2608.30769v1 Announce Type: new Abstract: LLM training is increasingly vulnerable to silent data corruption (SDC), yet existing protection methods largely treat Transformer computations uniforml

VFR-Audit: Verdict-Level Reliability for Fairness Audits in Hospital Length-of-Stay Prediction

arXiv:2608.30846v1 Announce Type: new Abstract: Fairness audits in clinical Artificial Intelligence convert continuous fairness metrics into binary pass-or-fail verdicts against operational thresholds