Search: “papers”

Whole-Body Bilateral Teleoperation with Multi-Stage Object Parameter Estimation for Wheeled Humanoid Locomanipulation

model-releasesarxiv-cs-ro

arXiv:2508.09846v2 Announce Type: replace Abstract: This paper presents an object-aware whole-body bilateral teleoperation framework for wheeled humanoid loco-manipulation. This framework combines who

25 Aug 2026

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Research

Why Personalization Matters: Cross-Subject Challenges in EMG-IMU-based HRI Activity Recognition

DGX agent

arXiv:2608.21620v1 Announce Type: new Abstract: This paper investigates wearable-based recognition of human activities and gestures to support Human-Robot Interaction (HRI) in object-handover and asse

researcharxiv-cs-ro

25 Aug 2026

Across-Design Uncertainty in Short Pricing Panels: Evidence from Simulated Price Trajectories

arXiv:2608.21334v1 Announce Type: new Abstract: Short observational pricing panels can contain many observations while offering only a small number of distinct price movements. This paper studies the

Applications

An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed Pigeon

arXiv:2504.16276v3 Announce Type: replace-cross Abstract: This paper presents a largely automated one-shot bird call classification pipeline, incorporating targeted manual quality control steps, desig

applicationsarxiv-cs-ai

// Applying Anthropic Primitives at Large Enterprises // Frontier models collapsed the cost of writing custom code. But they did not reduce …

// Applying Anthropic Primitives at Large Enterprises // Frontier models collapsed the cost of writing custom code. But they did not reduce the cost of reviewing and maintaining it. Each bespoke solut

model-releasesdair-ai--x

Aristotelian Manifolds: Leveraging Platonic Perceptual Features for Backpropagation Free Rapid Concept Learning

arXiv:2608.20682v1 Announce Type: new Abstract: This paper formalizes and systematically characterizes Aristotelian Manifolds, a generalized structural framework built upon the Platonic Representation

researcharxiv-cs-cv

Local Ai

Decision Tree and K-Means Analysis of Raman Spectra for Edible Oils: A Physics-Informed AI Approach

arXiv:2608.20440v1 Announce Type: cross Abstract: Authentication of edible oils in processed foods is important for food quality, fraud prevention, and regulatory compliance. This study establishes an

local-aiarxiv-cs-ai

Deep Learning Models Also Recall Features

arXiv:2608.20970v1 Announce Type: new Abstract: Recent work in mechanistic interpretability has studied how large language models recall facts stored in their weights. This paper argues that factual r

Demonstration-Guided Humanoid Stand-Up on an Emulated Deformable Surface

arXiv:2608.20852v1 Announce Type: new Abstract: This paper presents a reference-guided reinforcement learning framework to generate stand-up motion for a 29-DOF Unitree G1 humanoid on deformable soft

safetyarxiv-cs-ro

Foundation Models for Partial Causal Identification

arXiv:2608.20841v1 Announce Type: new Abstract: This paper investigates the development of causal foundation models for bounding the effect of interventions and counterfactuals from observational data

Infinite-dimensional generative diffusions via Doob's h-transform

arXiv:2602.06621v2 Announce Type: replace-cross Abstract: This paper introduces a rigorous framework for defining generative diffusion models in infinite dimensions via Doob's h-transform. Rather than

Metag: A dataset to build agentic meta-reviewing capabilities

arXiv:2608.20488v1 Announce Type: new Abstract: AI tools increasingly support tasks across the scientific research cycle, from experiment design and manuscript preparation to peer review. At the same

agentsarxiv-cs-lg

Optimizing Multi-Modality Trackers via Significance-Regularized Tuning

model-releasesarxiv-cs-cv

arXiv:2508.17488v4 Announce Type: replace Abstract: This paper tackles the critical challenge of optimizing multi-modality trackers by effectively adapting pre-trained models for RGB data. Existing fi

[R] Using AI as a spatial software generator to create 3D objects that are inherently programmable

researchr-machinelearning

I'm one of the co-authors of this paper. It's a seminal work in exploring the properties of 3D generated by LLMs via spatial programming. I've set up visual demonstrations of such 3D objects at: https

Applications

Root cause analysis via difference graph discovery from linear time-series data

arXiv:2608.21117v1 Announce Type: new Abstract: Root cause analysis aims to identify the mechanisms responsible for anomalies in complex dynamical systems. In this paper, we study root cause analysis

applicationsarxiv-cs-ai

Specification Portability Across LLM Development Agents: Cross-Agent Compatibility in Specification-Driven Software Migration

arXiv:2608.21208v1 Announce Type: cross Abstract: This paper investigates cross-agent specification portability using Oracle-to-PostgreSQL migration as a controlled software transformation task. The s

Quoting Drew Breunig

model-releasessimon-willison

Prior to Fable, it felt silly to waste too much time improving your coding harness or context strategies. A new model would arrive at the same price (or cheaper!) and paper over most of your problems.

23 Aug 2026

A 360-Degree Vision Dataset for Learning Yaw Control on GPS-Denied Micro-UAVs in Disaster-Response-Relevant Environments

arXiv:2608.19866v1 Announce Type: new Abstract: This paper presents a novel data-driven approach to camera-based autonomy for micro-drones in GPS-denied, radio-challenging indoor environments. The tar

agentsarxiv-cs-cv

From Atari to EVE Online: Building on 15 Years of AI Research in Games

model-releasesgoogle-deepmind

This paper traces the expansion of AI research in games over a 15‑year period, from early Atari benchmarks to contemporary MMORPGs such as EVE Online. It introduces SIMA 2, an agent designed to play,

Generating Diverse Personas for User Simulators to Test Interview Dialogue Systems

arXiv:2608.19549v1 Announce Type: new Abstract: This paper addresses the issue of the significant labor required to test interview dialogue systems. While interview dialogue systems are expected to be

researcharxiv-cs-cl

Keeping the Franka Emika Panda alive: a ROS 2 stack with a reliable position interface

arXiv:2608.19740v1 Announce Type: new Abstract: This paper presents an open-source software stack that restores ROS 2 support for the Franka Emika Panda robot while resolving the long-standing unrelia

researcharxiv-cs-ro

Llama.cpp DSpark PC Tree Fork (up to 3%-29.5% faster!)

model-releasesr-localllama

Hello gang, I made an implementation of DSpark PC Tree (Parent conditioned drafting tree). This is an implementation of this research paper: https://arxiv.org/abs/2608.02123 Unaffiliated, just found i

Multimodal Trajectory Planning for Surface Vehicles using Turning Circle-based Control Barrier Functions

arXiv:2608.19537v1 Announce Type: new Abstract: This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments. The pr

safetyarxiv-cs-ro

On the convergence of optimistic policy iteration for stochastic shortest path problem

arXiv:1808.08763v3 Announce Type: replace Abstract: In this paper, we prove some convergence results of a special case of optimistic policy iteration algorithm for stochastic shortest path problem. We

safetyarxiv-cs-lg

Tools

Simulation: the new Scaling Law — Joon Sung Park, Simile AI

Simile AI’s CEO Joon Sung Park describes how the company moved from the 2024 “Summer of Simulative AI” and its landmark *Generative Agents* paper to building digital twins that predict individual and

toolslatent-space

Spike-based Belief Propagation in Nonlinear Dynamical Systems

arXiv:2608.19907v1 Announce Type: new Abstract: This paper presents a Bayesian control framework that integrates spike-based dynamics with probabilistic inference for adaptive control. Bayesian infere

Transfer Learning in Nonparametric Regression with Deep ReLU Networks

arXiv:2608.20255v1 Announce Type: cross Abstract: This paper develops a general transfer learning framework for nonparametric regression with data consisting of multiple groups. Under the assumption t

WaveVerif: Acoustic Side-Channel based Verification of Robotic Workflows

arXiv:2510.25960v2 Announce Type: replace-cross Abstract: In this paper, we present a framework that uses acoustic side-channel analysis (ASCA) to monitor and verify whether a robot correctly executes

A Multi-Agent Platform for Automated Enterprise Analytics and Insight Generation

arXiv:2608.18740v1 Announce Type: new Abstract: This paper proposes a multi-agent framework built on CrewAI [1] for conversational business intelligence. Five specialized AI agents operate in a sequen

agentsarxiv-cs-ai

Tutorials

AI Can Learn Scientific Taste

arXiv:2603.14473v3 Announce Type: replace Abstract: Scientific discovery depends on expert judgement and foresight, which we call scientific taste: the ability to judge and propose research ideas with

tutorialsarxiv-cs-cl

Local Ai

AQuA's 'self-improvement' updates research state, not the agent LM. What should a local port freeze?

AQuA's preprint uses 'recursive self-improvement' for a bounded research loop. It does not say the research-agent LM rewrites its own weights. The paper separates three objects: The language model dri

local-air-localllama

Artifact-centered Claim-aware Observability for Autonomous Scientific Agents

arXiv:2608.18312v1 Announce Type: new Abstract: Autonomous scientific agents now increasingly propose ideas, write code, run experiments, analyze results, and even draft papers. Observe and audit thos

agentsarxiv-cs-cl

Budget-First Tariff Recommendation (BFTR): A Complete Algorithmic Framework for Telecom Plan Recommendation without Overcharging

arXiv:2608.18723v1 Announce Type: cross Abstract: Telecom operators traditionally offer predefined tariff grids, forcing users to choose from a limited set of plans. This paper proposes BFTR (Budget-F

DeGLIF for Label Noise Robust Node Classification using GNNs

arXiv:2506.00244v2 Announce Type: replace Abstract: Noisy labelled datasets are generally inexpensive compared to clean labelled datasets, and the same is true for graph data. In this paper, we propos

GS-VLA: Plug-and-Play Viewpoint Canonicalization for Frozen VLA Policies via Gaussian Splatting

arXiv:2608.19066v1 Announce Type: cross Abstract: This paper proposes a lightweight, plug-and-play framework that improves robustness to viewpoint shifts in Vision-Language-Action (VLA) policies witho

Large Language Model for Verilog Code Generation: Literature Review and the Road Ahead

arXiv:2512.00020v3 Announce Type: replace-cross Abstract: Code generation has emerged as a critical research area at the intersection of Software Engineering (SE) and Artificial Intelligence (AI), att

safetyarxiv-cs-ai

Multi-stage neural operator learning with application for convolutions

arXiv:2608.18851v1 Announce Type: new Abstract: Convolution integrals widely exist in applications, and to enable fast and accurate computations, this paper introduces two general multi-stage neural o

On the Triangle Inequality for the Jaccard Distance in Arbitrary Lattices

arXiv:2608.18194v1 Announce Type: new Abstract: This paper presents new theoretical results on generalizing the Jaccard distance for lattices and real valuations. We demonstrate that when the valuatio

Pedagogical AI in Mental Health: A Tri-Stream Fine-Tuned LLM Framework for Automated Clinical Supervision and Risk Triage

arXiv:2608.18438v1 Announce Type: cross Abstract: Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a 'supervision gap' where novice therapists manage high

Applications

Position: AI Leaderboards Are Underserving the Global South: A Case Study from India

arXiv:2608.18117v1 Announce Type: new Abstract: This position paper argues that AI leaderboards are structurally ill-suited to serving the Global South because they lack independent governance, confli

applicationsarxiv-cs-ai

Position: Collusion Risks Among AI Reasoning Agents Justify Certification Requirements for Making Market Decisions

arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be requi

Position: Multi-Agent Systems Should Prioritize Concurrency Control

arXiv:2608.18092v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often reduces reliability. This position paper argues that many MA

agentsarxiv-cs-ai

Real-Time Control-Constrained DDP for Underactuated Balancing of Legged Robots

arXiv:2608.18552v1 Announce Type: new Abstract: This paper presents a real-time control-constrained Differential Dynamic Programming (DDP) framework for underactuated legged robots. To address the lim

researcharxiv-cs-ro

Sanyu Studio: A Multi-Agent System for Art-Historical Narrative Construction

arXiv:2608.18677v1 Announce Type: new Abstract: Amid concerns that generative AI may standardize art interpretation, this paper examines whether LLM-based interaction can support plural art-historical

agentsarxiv-cs-ai

Tatarstan Toponyms: A Bilingual Dataset and Hybrid RAG System for Geospatial Question Answering

model-releasesarxiv-cs-cl

arXiv:2605.05962v2 Announce Type: replace Abstract: This paper addresses end-to-end geospatial question answering over multilingual toponymic data. We introduce a bilingual (Russian-Tatar) dataset of

Tensor Field Models

arXiv:2608.18808v1 Announce Type: new Abstract: This paper introduces Tensor Field Models (TFMs), realization-level Mathematical Structures in which a learned Operator maps a product of admissible com

A Residual Learning Approach for Unsteady Aerodynamic Load Prediction

model-releasesarxiv-cs-lg

arXiv:2608.17894v1 Announce Type: cross Abstract: This paper investigates the feasibility of using residual learning to improve unsteady aerodynamic load prediction for aeroelastic applications. The m

19 Aug 2026

Adaptive surrogate modeling for high-dimensional spatio-temporal output

arXiv:2608.17250v1 Announce Type: cross Abstract: This paper develops an adaptive surrogate modeling method for problems with very high-dimensional spatio-temporal outputs. The analysis of spatio-temp