Search: “papers”

Semantic- and Density-Aware Planning for Accessibility-Preserving Multi-Object Placement

arXiv:2608.16741v1 Announce Type: new Abstract: Long-term manipulation planning requires robots to reason not only about immediate task success but also about how current decisions affect future inter

applicationsarxiv-cs-ro

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Agents

Semantic Uncertainty-Guided Orchestration in Hierarchical Multi-Agent Systems

DGX agent

arXiv:2608.14707v1 Announce Type: new Abstract: As large language model (LLM)-based multi-agent systems become increasingly capable, coordinating agents under uncertainty becomes a fundamental challen

agentsarxiv-cs-ai

18 Aug 2026

Industry

Something super exciting happened quietly on HF over the past month: AI agents became AI builders, and they did it in the open! During our I…

Something super exciting happened quietly on HF over the past month: AI agents became AI builders, and they did it in the open! During our ICML reproduction challenge, 1,221 humans teamed up with codi

industryclem-delangue--x

Steering the Flow: Inverting Face Recognition Models via Gradient-Guided Flow Matching

arXiv:2608.16791v1 Announce Type: cross Abstract: Model Inversion Attacks (MIAs) aim to reconstruct representative training samples of target identities from face recognition models, exposing critical

Stitch the Fragments: One-Shot Hierarchical Federated Clustering

arXiv:2601.06404v2 Announce Type: replace Abstract: Federated Clustering (FC) faces a critical bottleneck in real-world scenarios, i.e., global clusters are rarely intact, often fragmenting into incom

T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework

arXiv:2608.14953v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, an

TDD-Agent: Test-Driven Reasoning for Code Generation

arXiv:2608.16742v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable progress in code generation, yet ensuring correctness in complex, repository-level tasks remains

Agents

The Authority Resolution Framework: A Five-Domain Ontology for Governing Who and What Decides, at Scale

arXiv:2608.15832v1 Announce Type: new Abstract: As AI systems become increasingly capable of autonomous action, determining whether an agent is technically capable of performing an action is insuffici

agentsarxiv-cs-ai

The Benchmark Trap: Structures of Power and Injustice in AI Evaluations

arXiv:2608.15326v1 Announce Type: new Abstract: Artificial intelligence (AI) benchmarks are not neutral tools of evaluation but socio-technical artefacts that shape competition, power, and research pr

The Commercial Tax: Rent-vs-Own Blind Spots in Multi-Hop Retrieval Benchmarks

model-releasesarxiv-cs-cl

arXiv:2608.16096v1 Announce Type: cross Abstract: Enterprises connect language models to their own data through retrieval. The benchmarks that rank multi-hop retrieval systems leave out two facts a bu

The Ethical Decision Head: Operationalizing Normative Ethics in Autonomous Vehicles via Reinforcement Learning from Human Feedback

arXiv:2608.16710v1 Announce Type: new Abstract: As autonomous vehicles (AVs) approach Level 4 and Level 5 operational capability [SAE International, 2018], their on- board decision systems must handle

safetyarxiv-cs-lg

The Fake Friend Dilemma: Relational Trust and the Political Economy of Conversational AI

arXiv:2601.03222v2 Announce Type: replace-cross Abstract: As conversational AI systems become a larger part of the media landscape, they raise questions about whose interests they serve and the risks

safetyarxiv-cs-ai

The Quantum Shortcut: Complex Phase-State Dynamics Reduce the Optimization Steps of Sequence Models

arXiv:2608.14691v1 Announce Type: new Abstract: Sequence models are conventionally distinguished by their backbone, the mechanism that routes information across positions, such as attention or recurre

researcharxiv-cs-lg

The Unwritten Benchmark: A New Challenge for Multimodal Machine Learning in Abstract Perceptual Reasoning

arXiv:2608.14558v1 Announce Type: new Abstract: Current multimodal models have demonstrated remarkable proficiency in recognizing static visual and auditory content. However, their capacity for abstra

Throwing a Tight Spiral American Football by a Humanoid Robot

arXiv:2608.16642v1 Announce Type: new Abstract: Accurate throwing of the American football requires precise regulation of release conditions, where coupled linear and angular momentum determine flight

safetyarxiv-cs-ro

Time-Aware Validation of Machine Learning Fuel Consumption Models: Evidence from 1,Hz Operational Data, CCGS extit{Sir Wilfrid Laurier}

arXiv:2608.16833v1 Announce Type: new Abstract: Ship fuel consumption (SFC) prediction supports vessel operation optimisation, emissions estimation, and decision support systems (DSS) for sustainable

applicationsarxiv-cs-lg

Time to Reason: Scalable Neurosymbolic Learning for LTLf via Fuzzy Semantics

arXiv:2608.16443v1 Announce Type: new Abstract: Neurosymbolic (NeSy) Artificial Intelligence aims to integrate Deep Learning (DL) architectures with symbolic reasoning. While initial NeSy approaches h

Towards a Unified Understanding of Robot Manipulation: A Comprehensive Survey

arXiv:2510.10903v2 Announce Type: replace Abstract: Embodied intelligence has witnessed remarkable progress in recent years, driven by advances in computer vision, natural language processing, and the

safetyarxiv-cs-ro

Towards Standardized Evaluation in Automated Domain Modeling: Introducing a Benchmark

arXiv:2608.15255v1 Announce Type: new Abstract: Domain modeling plays an essential role in domain-driven design, capturing essential entities and their relationships within a specific domain. Despite

Towards Zero-Shot Domain Generalization for ID Cards Presentation Attack Detection

model-releasesarxiv-cs-cv

arXiv:2608.16591v1 Announce Type: new Abstract: Presentation-Attack Detection (PAD) for national ID cards is limited by the lack of publicly available genuine samples, making it difficult for systems

TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions

arXiv:2608.15391v1 Announce Type: new Abstract: Large language model (LLM)-assisted energy-management tools can translate natural-language context into structured grid commands, but syntactic validity

safetyarxiv-cs-ai

Unified Pedestrian Path Prediction Using Inverse Reinforcement Learning

arXiv:2608.15929v1 Announce Type: new Abstract: Pedestrian path prediction is crucial for enhancing the safety of autonomous vehicles and advanced driver-assistance systems. Previous studies explored

Validation-Frontier Representation Selection under Constrained Observation

arXiv:2608.15095v1 Announce Type: new Abstract: AI systems deployed outside clean benchmark settings often rely on observations that are incomplete, unstable, costly, or degraded by monitoring failure

WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales

arXiv:2505.04608v5 Announce Type: replace-cross Abstract: Responsibly deploying artificial intelligence (AI) / machine learning (ML) systems in high-stakes settings arguably requires not only proof of

applicationsarxiv-cs-ai

When Do LLMs Apply the Wrong Law? Diagnosing LLM Failures in Temporal Legal Reasoning

arXiv:2608.14610v1 Announce Type: new Abstract: Legal reasoning tasks such as legal judgment prediction (LJP) require identifying the temporally correct version of the law governing a case -- a capabi

Local Ai

When Is Shallow Enough? Adaptive Split Federated Learning with Client-Specific Sufficiency Estimation

arXiv:2608.15639v1 Announce Type: cross Abstract: extit{Split Federated Learning} (SFL) enables distributed model training by splitting networks between the server and clients. However, under client h

local-aiarxiv-cs-ai

Which Question Is Your Attention Metric Answering? Attention Rows as Compositional Data

arXiv:2608.14712v1 Announce Type: cross Abstract: Each row of a transformer's attention matrix is a probability distribution over tokens, and in trained models most of that probability lands on a sing

Agents

Workspace Topology as an Attack Vector in Agentic Coding Assistants

arXiv:2608.14876v1 Announce Type: cross Abstract: Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This

agentsarxiv-cs-ai

Xemo-Talker: Unlock Emotions Explicitly for Audio-Driven Talking Portrait Synthesis

arXiv:2608.14700v1 Announce Type: new Abstract: Precise emotion control in audio-driven talking heads remains a challenge due to the reliance on implicit emotion regulation in existing systems, which

researcharxiv-cs-cv

zLend: A Dual-Scope Cash-Flow Reconstruction Framework for On-Chain Credit Underwriting

arXiv:2608.16856v1 Announce Type: cross Abstract: Decentralized lending lacks a credit bureau: a borrower's capacity to repay must be inferred entirely from public on-chain activity, without income ve

Local Ai

A Configuration-First Framework for Reproducible, Low-Code Localization

arXiv:2510.25692v4 Announce Type: replace-cross Abstract: As machine learning (ML) increasingly underpins critical applications, credible, comparable, and repeatable experimental results become more i

local-aiarxiv-cs-lg

A Data-Driven Algorithm for Model-Free Control Synthesis

arXiv:2602.13157v2 Announce Type: replace-cross Abstract: Presented is an algorithm to synthesize the optimal infinite-horizon LQR feedback controller for continuous-time systems. The algorithm does n

researcharxiv-cs-ro

A Generalized Parallelogram Rule for Proportional Analogies on Riemannian Manifolds

arXiv:2608.14220v1 Announce Type: new Abstract: Analogies are quaternary relations of the form 'a is to b as c is to d', usually denoted a : b :: c : d. This notion is formalized in particular with th

A Hybrid LLM-Based Framework for Automated Security Annotation Generation in Business Process Models

arXiv:2608.14370v1 Announce Type: cross Abstract: The modelling and analysis of secure business processes require the incorporation of security annotations into process models. Although BPMN extension

A Survey of Large Models in Sports

arXiv:2608.14377v1 Announce Type: new Abstract: Sports have witnessed growing global enthusiasm in recent years, serving as a vital force for physical health, cultural exchange, social connection, and

researcharxiv-cs-cl

A Systematic Comparison of Training Objectives for Out-of-Distribution Detection in Image Classification

arXiv:2603.07571v3 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection is critical in safety-sensitive applications. While this challenge has been addressed from various perspec

safetyarxiv-cs-ai

A Year in LLM Serving: Workload Evolution, Caching and Load-Balancing

arXiv:2608.13573v1 Announce Type: new Abstract: Large Language Model (LLM) serving has become a critical cloud workload, and realistic traces are essential for motivating and benchmarking serving syst

applicationsarxiv-cs-ai

Act2Intention: A Benchmark For Developing Active Mobile Agents Through Inferring User Intention from GUI Actions

arXiv:2608.14132v1 Announce Type: cross Abstract: Mobile GUI Agents powered by multimodal large language models (MLLMs) show promise in human-computer intelligence. However, current research primarily

Adaptive Protection for Evolutionary Feature Construction in Symbolic Regression with Application to Credit Classification

arXiv:2608.14209v1 Announce Type: new Abstract: Evolutionary feature construction has shown strong promise in symbolic regression by automatically discovering informative transformations of input feat

Adversarial Learning of Classifier-Free Guidance Schedules

arXiv:2608.14038v1 Announce Type: new Abstract: Modern text-to-image diffusion models rely on classifier-free guidance (CFG) to achieve high image fidelity and text alignment. However, CFG typically a

safetyarxiv-cs-lg

Local Ai

Agentao: A Governed Local-First Runtime for Tool-Using LLM Agents

arXiv:2608.13574v1 Announce Type: new Abstract: LLM agents increasingly operate as execution systems that invoke tools, modify local state, use persistent memory, and interact with external protocols.

local-aiarxiv-cs-ai

AI-Assisted Discovery and Construction of a Counterexample to the Convergence of Three-Block ADMM with the Identity Matrix as its Third Constraint Block

arXiv:2608.14396v1 Announce Type: cross Abstract: The alternating direction method of multipliers (ADMM), as a landmark algorithm, has attracted tremendous research attention and extensive practical a

AI Research Preference Models

arXiv:2608.13940v1 Announce Type: new Abstract: AI research agents (AIRA) can now propose, implement, and evaluate their own machine learning experiments, but progress on frontier tasks is throttled b

Hardware

Announcing AItonomy Foundation. We are PhD students and postdocs at Stanford, Princeton and Oxford, building a nonprofit research organizati…

Announcing AItonomy Foundation. We are PhD students and postdocs at Stanford, Princeton and Oxford, building a nonprofit research organization for AI4Science and Science4AI — and connecting early-care

hardwareemad-mostaque--x

Approximate Muon with low-rank adapters

arXiv:2608.14492v1 Announce Type: new Abstract: The Muon optimizer shows clear benefits versus alternatives when pretraining neural networks. However, it is used less frequently for parameter-efficien

Architecture and Affordances of PLAUD: Performative Latents and Unsupervised DDSP

arXiv:2608.13724v1 Announce Type: cross Abstract: PLAUD (Performative Latents and Unsupervised DDSP) is a neural synthesizer and Max for Live instrument for live electronic music, built on NoiseBandNe

researcharxiv-cs-lg

Benchmarking data-driven material models on the classic Treloar dataset

arXiv:2608.14063v1 Announce Type: new Abstract: Machine learning is rapidly reshaping constitutive modeling, offers new ways to learn material behavior directly from experimental data, and challenges

Capacity-Dependent Effects of Data Selection for Reasoning

arXiv:2608.13721v1 Announce Type: cross Abstract: In reasoning supervised fine-tuning, candidate responses for the same instruction can differ substantially in how well they match the student's curren