Search: “papers”

Towards a Unified Taxonomy of Agricultural Harvesting Technologies: Linking Physical Interaction, Automation, and Selectivity

arXiv:2610.13688v1 Announce Type: new Abstract: Harvesting technologies have evolved from conventional mechanized systems based on bulk mechanical interaction toward increasingly automated and robotic

researcharxiv-cs-ro

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Research

Towards Defining, Measuring, and Leveraging Creativity in AI Applications

DGX agent

arXiv:2610.12845v1 Announce Type: new Abstract: Despite extensive research, computational creativity still lacks a conceptually grounded, practically relevant, and empirically applicable formal defini

researcharxiv-cs-ai

12 Oct 2026

Towards Enriching Design-Time Models with Evidence from Simulation and Operational Activities

arXiv:2610.13456v1 Announce Type: new Abstract: Cyber-Physical Systems are developed through multiple model based activities, comprising several stages of development. As the development progresses th

researcharxiv-cs-cl

Unreliable Narrator Framing as a Cost-effective Mechanism for Satire Explanation of Australian and American Satirical News

model-releasesarxiv-cs-cl

arXiv:2610.12863v1 Announce Type: new Abstract: Satirical news is a unique form of misinformation: it is intended to be humorous by the original publication source but can be misinterpreted. Explanati

Verifiable Retrieval for Legal Reasoning through Structure-driven Knowledge Graph

arXiv:2610.13695v1 Announce Type: new Abstract: Any automation within reliability-critical contexts such as medicine or law has to be transparent and verifiable. Despite their advantages, current LLM-

applicationsarxiv-cs-cl

Agents

When Faster Decisions Do Not Make Better Agents: An Empirical Study of Jev in Agent Workflows

arXiv:2610.13092v1 Announce Type: new Abstract: AI agents depend on repeated decisions to accomplish tasks, with large language models (LLMs) commonly serving as their core decision makers. The recent

agentsarxiv-cs-ai

AI solved open mathematical problems. But the biggest surprise came afterwards. A team at Google DeepMind has used AI to resolve 9 open Erdő…

model-releasesyohei-nakajima--x

AI solved open mathematical problems. But the biggest surprise came afterwards. A team at Google DeepMind has used AI to resolve 9 open Erdős problems, including questions that had remained unsolved f

10 Oct 2026

Agents

“The field of artificial life is a very long-term bet on intelligence.” 🐙 Our former intern Akarsh Kumar recently joined @MLStreetTalk to d…

“The field of artificial life is a very long-term bet on intelligence.” 🐙 Our former intern Akarsh Kumar recently joined @MLStreetTalk to discuss the intersection of evolution and automated search for

agentsdavid-ha--x

10 Oct 2026

Typesafe ai raised 870m $ on hype (jev)

https://typesafe.ai/blog/series-ai Meanwhile one of the reddit members apparently developed the same architecture a year ago: https://www.reddit.com/r/LocalLLaMA/s/8zQXqCNDlb Looks like ai valuation n

local-air-localllama

10 Oct 2026

A General widetilde{Omega}(sqrt{T gamma_T}) Lower Bound for Kernel Bandits

arXiv:2610.11082v1 Announce Type: cross Abstract: The kernel bandit problem consists of sequentially optimizing an unknown function with noisy feedback, where the function has bounded norm in a given

A Reconfigurable Fabric Based Pneumatic Actuator with Button Fastened Constraint Modules for Multi Mode Actuation

arXiv:2610.11054v1 Announce Type: new Abstract: Soft pneumatic actuators are widely used in soft robotics. However, their actuation modes are typically fixed by internal chamber designs or reinforceme

researcharxiv-cs-ro

A Structural Theory of Cognitive Representation and Problem Solving,Contexts, Invariance, and the Knowledge Space

arXiv:2610.12306v1 Announce Type: new Abstract: Learning and problem solving depend critically on the structure of internal representations. While many modern data-driven artificial systems achieve st

researcharxiv-cs-ai

Accelerating Non-Smooth and Heavy-Tailed Sampling

arXiv:2610.11139v1 Announce Type: cross Abstract: Anchored Langevin dynamics (ALD) is useful for non-smooth sampling where the density of the target distribution is possibly non-differentiable and hea

ActionCodec: What Makes for Good Action Tokenizers

arXiv:2602.15397v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models leveraging the native autoregressive paradigm of Vision-Language Models (VLMs) have demonstrated superior

Adaptive Multi-Discriminator WGAN Framework for Resource-Constrained Internet of Vehicles Using Reinforcement Learning and Game Theory

arXiv:2610.10926v1 Announce Type: new Abstract: Managing machine learning workloads as a network service introduces a resource-orchestration problem distinct from conventional model training; which no

applicationsarxiv-cs-lg

An Efficient Quantum Circuit for Flow Model Execution Using Quantum Neural Networks

arXiv:2610.11537v1 Announce Type: cross Abstract: Flow models generate trajectories from an initial distribution to a target distribution by solving an ordinary differential equation defined by a velo

An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment

arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In me

Attributing HOW, Not Just WHICH: Counterfactual Response Trajectories for Diffusion Models

arXiv:2610.11238v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in image generation, yet tracing their outputs to individual training examples remains challenging. Ex

researcharxiv-cs-cv

Automated Assembly Instruction Generation from CAD Models Using Grounded Large Language Models: A Human-in-the-Loop Framework

arXiv:2610.11896v1 Announce Type: new Abstract: Assembly documentation is a downstream manufacturing artifact that is still usually authored by interpreting CAD models by hand. Structured product data

applicationsarxiv-cs-lg

Barron Optimal Transport I: Generative Modeling

arXiv:2610.10875v1 Announce Type: new Abstract: Motivated by recent applications in generative modeling and sampling, we introduce a framework for optimal measure transport where cost captures the not

Beyond Distributional Fidelity: Causal-Penalized Diffusion for Synthetic Tabular Data

arXiv:2610.11407v1 Announce Type: cross Abstract: Synthetic tabular generators are commonly optimized for distributional fidelity, but statistical similarity alone does not guarantee preservation of c

Beyond Imitation: A Framework and Benchmark for LLM-Assisted Peer Review

arXiv:2610.11087v1 Announce Type: new Abstract: The rapid growth of scientific publishing has strained peer review, particularly in machine learning, raising concerns about declining review quality an

Beyond QAOA: A Review of AI and Quantum Computing for Adaptive Combinatorial Optimization

arXiv:2610.11759v1 Announce Type: cross Abstract: Near-term quantum approaches to combinatorial optimization are limited by qubit counts, circuit fidelity, sampling cost, and the difficulty of encodin

BRACE: Differential Privacy for Dense Associative Memory with LSR Energy

arXiv:2610.11218v1 Announce Type: cross Abstract: Dense associative memory (DAM) provides an energy-based framework for memory retrieval with close connections to attention mechanisms in modern artifi

Can Jev be Your Q or Policy in Reinforcement Learning?

arXiv:2610.11692v1 Announce Type: cross Abstract: Foundation models supply reinforcement learning (RL) with priors that mitigate its longstanding weaknesses in sample efficiency and transfer, but thei

Census-Based Population Autonomy For Distributed Robotic Teaming

arXiv:2511.02147v2 Announce Type: replace Abstract: Collaborating teams of robots show promise due to their ability to complete missions more efficiently and with improved robustness, attributes that

local-aiarxiv-cs-ro

Characterizing Overconfident Failure in LLM-Based Code Generation

arXiv:2610.11300v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for automated code generation, but generated programs can appear syntactically plausible while stil

local-aiarxiv-cs-ai

Complexity of Grounded Semantics and Preferred Semantics in Finitary Argumentation Frameworks

arXiv:2610.12008v1 Announce Type: new Abstract: Abstract argumentation frameworks (AFs) introduced by Dung provide a formal foundation for non-monotonic reasoning in artificial intelligence. While dec

researcharxiv-cs-ai

Cost-Aware Mixture-of-Experts Coordination for Model Markets

arXiv:2610.11908v1 Announce Type: cross Abstract: Existing model marketplaces typically trade and select individual models as indivisible units, limiting their ability to exploit complementarities amo

DaCe-DT: Data-Centric Offline Multi-Task Reinforcement Learning via Adaptive Prompts and Trajectory Correction for Heterogeneous Tasks

arXiv:2610.11085v1 Announce Type: new Abstract: Offline multi-task reinforcement learning (Offline MTRL) heavily depends on the quality and distribution of pre-collected data. However, existing method

safetyarxiv-cs-lg

DAMP: Humanoid Locomotion via Denoised Belief Learning and Adversarial Motion Priors

arXiv:2610.11505v1 Announce Type: new Abstract: Humanoid robots possess the structural capability to traverse complex terrains. However, achieving stable t raversal without relying on perceived inform

safetyarxiv-cs-ro

Deep Learning vs. Statistical Models for Multi-Horizon Price Forecasting of Second-Hand Electronics: A Systematic Benchmark

arXiv:2610.10727v1 Announce Type: cross Abstract: Forecasting resale prices of used electronics is critical for subscription-based platforms where pricing errors translate directly into risk. Unlike s

Density Ratio Estimation with Stein Displacement Fields

arXiv:2610.12437v1 Announce Type: cross Abstract: Density ratios quantify distribution shift from a probability-mass point of view, whereas displacement fields describe, from a dynamical point of view

DEX: Digit-Level Early Exit for Energy-Efficient MSDF Neural Network Inference

arXiv:2610.11748v1 Announce Type: cross Abstract: U-Net inference for brain-tumor segmentation requires billions of multiply-accumulate operations, motivating hardware that can reduce computation dyna

safetyarxiv-cs-ai

Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation

arXiv:2610.11067v1 Announce Type: new Abstract: Prompt learning is a popular method for adapting foundation models, but learned prompts are typically task-specific and fail to generalize to new classe

researcharxiv-cs-cv

Digital Twin for Pre-Deployment Validation of AI-Driven Safety-Critical Industrial Edge Control Loops

arXiv:2610.11934v1 Announce Type: cross Abstract: Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intellige

safetyarxiv-cs-ro

Distributed Relative Localization Based on Ultra-WideBand and LiDAR for Multi-robot with Limited Communication

arXiv:2610.11141v1 Announce Type: new Abstract: Relative localization is crucial for a multi-robot system to collaboratively perform tasks, such as exploration and formation. However, this is highly c

researcharxiv-cs-ro

Distributed Relative Localization for Homogeneous Multi-Robot Systems through UWB Ranging and Limited Communications

arXiv:2610.11308v1 Announce Type: new Abstract: Accurate and reliable relative localization is crucial for multi-robot applications like exploration, search, and rescue missions. LiDAR-based solutions

applicationsarxiv-cs-ro

Dynamic Free-Rider Detection in Cross-Silo Federated Learning via Simulated Attack Patterns

arXiv:2604.04611v3 Announce Type: replace Abstract: Federated learning (FL) enables multiple clients to collaboratively train a global model by aggregating local updates without sharing private data.

local-aiarxiv-cs-lg

DynaTE: Accelerating Diffusion LLMs via Dynamic Token Execution

arXiv:2610.11284v1 Announce Type: cross Abstract: Diffusion-based LLMs (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) LLMs by enabling bidirectional parallel refinemen

researcharxiv-cs-ai

Efficient quadratic entropy with distance sketches

arXiv:2610.11976v1 Announce Type: cross Abstract: We detail scalable methods for approximating the quadratic entropy p^T d p for arbitrary distributions p and common distances d of negative type. We f

Enabling Quantum Natural Language Processing for Hindi Language

arXiv:2312.01221v2 Announce Type: replace Abstract: Quantum Natural Language Processing (QNLP) is taking huge leaps in solving the shortcomings of classical Natural Language Processing (NLP) technique

researcharxiv-cs-cl

Tutorials

Estimating great expectations under autoregressive language models with potentials

arXiv:2610.11399v1 Announce Type: new Abstract: Many applications of language models hinge not on individual samples but on the expectation of a test functional under the model. Estimating such expect

tutorialsarxiv-cs-ai

Evaluating Rubric Generation with Interventional Transfer

arXiv:2610.10809v1 Announce Type: new Abstract: Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale,

Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology

arXiv:2610.12022v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external

Explaining the Saliency Map Sparsity of Adversarially-Trained Neural Networks

arXiv:2610.10666v1 Announce Type: new Abstract: Understanding why deep neural networks make a given prediction is of great importance for their safe deployment. In computer vision, saliency maps, whic

Tutorials

Exploiting Gradients in Bayesian Inference of Expensive Simulators

arXiv:2610.12076v1 Announce Type: new Abstract: Simulators based on differential equations are ubiquitous in science and engineering. They are often used in simulation-based inference to evaluate the

tutorialsarxiv-cs-lg

Fact over Fiction: Detection of Pathological Hallucinations in Sinhala-to-English Neural Machine Translation

model-releasesarxiv-cs-cl

arXiv:2610.11389v1 Announce Type: new Abstract: Neural Machine Translation (NMT) models, while capable of producing highly fluent outputs, remain vulnerable to hallucinations, which are translations t