Search: “papers”

Sierpinski--Knopp Wasserstein Distance for Persistence Diagrams and Applications to 2-Wasserstein Approximation

model-releasesarxiv-cs-lg

arXiv:2609.01528v1 Announce Type: cross Abstract: This paper introduces the Sierpinski-Knopp (SK) Wasserstein distance, a fast metric between persistence diagrams. The SK-Wasserstein distance, denoted

2 Sept 2026

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Safety

Socrates went Nuclear: Comparing Interaction Strategies for AI systems in a Learning Context using Brain Sensing

DGX agent

arXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud

safetyarxiv-cs-ai

2 Sept 2026

Stochastic complexity of vectors containing cluster structure

arXiv:2609.00084v1 Announce Type: new Abstract: This paper studies the problem of computing the stochastic probability (shortest code length) of the encoded vectors containing cluster structure using

researcharxiv-cs-lg

2 Sept 2026

A Dual-Cam Parallel Elastic Actuator with Shared Gas-Spring Compensation for Humanoid Ankles

arXiv:2608.30832v1 Announce Type: new Abstract: To improve torque capacity and energy efficiency of humanoid ankles, this paper proposes a 2-DoF parallel elastic actuator (PEA). The main novelty of th

researcharxiv-cs-ro

A Simple Method to Enhance Pre-trained Language Models with Speech Tokens for Classification

arXiv:2512.07571v3 Announce Type: replace Abstract: This paper presents a simple method that allows to easily enhance textual pre-trained large language models with speech information, when fine-tuned

researcharxiv-cs-cl

Asymmetric Within-Document Predictive Learning for Scientific Document Representation

arXiv:2608.28625v1 Announce Type: cross Abstract: We study predictive pretraining for scientific document representation using the discourse structure of papers. We propose SciJEPA, a citation-free fr

safetyarxiv-cs-ai

Agents

Can LLM Agents Discover? Evaluating Creativity on ML Engineering Tasks

arXiv:2608.30047v1 Announce Type: new Abstract: Recent AI systems promise autonomous scientific discovery, claiming to discover algorithms and produce research papers, yet understanding whether they e

agentsarxiv-cs-ai

CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification

arXiv:2502.18176v3 Announce Type: replace-cross Abstract: In this paper, we aim to build an adversarially robust zero-shot image classifier. We ground our work on CLIP, a vision-language pre-trained e

researcharxiv-cs-ai

Clustering as Approximation by Constrained Projectors: Theory and Guarantees

arXiv:2608.29102v1 Announce Type: new Abstract: This paper develops a unified theoretical framework showing that a broad family of clustering methods, including k-means, fuzzy c-means, kernel k-means,

researcharxiv-cs-ai

Local Ai

Cognitively-Grounded On-Device Runtime Learning for Ground Robots in Unknown Physical Environments

arXiv:2608.28677v1 Announce Type: new Abstract: This paper presents l{CogRun}, a framework that enables safety-critical ground robots to perform cognitively-grounded runtime learning entirely on edge-

local-aiarxiv-cs-ro

COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning

arXiv:2608.30109v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on extensive scientific research are increasingly integrated as assistants for scientific discovery. However, most

ContextBias: Controlled Evaluation of Bias Persistence Under Context Shift in Text-to-Image Models

arXiv:2608.29847v1 Announce Type: cross Abstract: Text-to-image models learn associations between concepts - in the case of this paper, people's professions, which we refer to as roles - and visual at

DARP: A Calibrated Dual-Arm RGB-D-IR Dataset for Multi-View Robotic Perception

arXiv:2608.31002v1 Announce Type: cross Abstract: Robotic perception from a single viewpoint is often limited by self-occlusion and incomplete surface visibility. This paper presents DARP(Dual-Arm Rob

FigMirror: Ground It, Code It, Plot It

arXiv:2608.28814v1 Announce Type: cross Abstract: Converting scientific figures into executable code has gained increasing attention, yet existing methods primarily focus on reproducing the reference

Applications

Free Speech and Artificial Intelligence

arXiv:2608.28973v1 Announce Type: cross Abstract: Philosophers and legal scholars are engaged in debates about the implications of artificial intelligence for freedom of expression. This paper analyze

applicationsarxiv-cs-ai

Local Ai

FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time

arXiv:2510.23515v3 Announce Type: replace Abstract: This paper proposes FreeFuse, a training-free framework for multi-subject text-to-image generation through automatic fusion of multiple subject LoRA

local-aiarxiv-cs-cv

Generating Workflow DAGs from Natural Language with Non-Reasoning LLMs

arXiv:2608.30250v1 Announce Type: new Abstract: This paper addresses the problem of translating natural-language routing rules written by business administrators into executable workflow graphs for en

GFlowNets and variational inference

arXiv:2210.00580v4 Announce Type: replace Abstract: This paper builds bridges between two families of probabilistic algorithms: (hierarchical) variational inference (VI), which is typically used to mo

HorizonNet for visual terrain navigation

arXiv:2608.30471v1 Announce Type: new Abstract: This paper investigates the problem of position estimation of unmanned surface vessels (USVs) operating in coastal areas or in the archipelago. We propo

How Prolific Sellers Self-Present: Dissecting the Communication Patterns of 1.6 Million Reverb Listings

arXiv:2608.29952v1 Announce Type: new Abstract: The current paper draws on self-presentation theory and warranting theory to evaluate how the language patterns in an online marketplace reflect seller

researcharxiv-cs-cl

Hybrid Offline-Online Multi-Agent Decision Transformers for Wireless Resource Management

arXiv:2608.28878v1 Announce Type: cross Abstract: This paper develops a hybrid offline-online multi-agent reinforcement learning framework based on decision transformers. The policy is first pretraine

safetyarxiv-cs-ai

Interpretable Predictability-Based AI Text Detection: A Replication Study

arXiv:2603.15034v2 Announce Type: replace-cross Abstract: This paper replicates and extends the system used in the AuTexTification shared task for authorship attribution of machine-generated texts. Ex

Memory-First Fact-Checking: A Knowledge-Graph-Grounded Multi-Agent System for Misinformation Detection

arXiv:2608.29617v1 Announce Type: cross Abstract: This paper introduces a hybrid fact-checking framework that integrates Knowledge Graph-based semantic memory with adversarial multi-agent reasoning fo

Tutorials

MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors

arXiv:2406.00434v4 Announce Type: replace Abstract: In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes from a casually captured monocular video. Previous monocula

tutorialsarxiv-cs-cv

Motion-Saliency Complementary Masked Modeling for Point Cloud Video Understanding

arXiv:2608.30279v1 Announce Type: new Abstract: Point cloud video representation learning is crucial for 3D dynamic scene understanding. In this paper, we propose MoSaiC, a novel Motion-Saliency Compl

Multiclass Linear Perceptrons with Multiplicative Margins

arXiv:2608.30028v1 Announce Type: new Abstract: This paper introduces a family of multiclass linear Perceptron classifiers with a multiplicative margin mechanism (MMPerc), as an alternative to standar

Applications

MURANO: Design, Run, and Reproduce Mechanistic Interpretability Experiments as Composable Pipelines

arXiv:2608.30662v1 Announce Type: new Abstract: This paper presents Murano, an open source framework for designing, running, and reproducing mechanistic interpretability studies of large language mode

applicationsarxiv-cs-cl

Hardware

NepScript Genesis: Neural Architecture Search for Handwritten Devanagari Digit Synthesis

arXiv:2608.29540v1 Announce Type: new Abstract: This paper introduces NepScript Genesis, a Neural Architecture Search (NAS) framework for automated Generative Adversarial Network (GAN) discovery, appl

hardwarearxiv-cs-cv

PaperBanana-Interact: Scientific Diagram Refinement with Multi-Turn Human Feedback

arXiv:2608.30241v1 Announce Type: new Abstract: Recent efforts have aimed to automate scientific diagram generation from paper content (Lin et al., 2026; Zhu et al., 2026a). However, fully satisfying

PaperGym: Rubric-Centered Evolution for Research-Plan Generation

arXiv:2608.31119v1 Announce Type: new Abstract: Research planning is the decisive capability of AI scientists. Yet a research plan admits no verifiable answer, so reinforcement learning lacks the envi

Applications

PromptKWS: A Novel Prompt-Guided Open-Vocabulary Keyword Spotting Framework

arXiv:2608.28640v1 Announce Type: cross Abstract: In this paper, we present PromptKWS, a novel Prompt-guided keyword spotting (KWS) framework to improve the accuracy of open vocabulary KWS systems. In

applicationsarxiv-cs-ai

Provably Safe Decentralized Contingency MPC under State-Only Information and Limited Sensing for Nonlinear Multi-agent Systems

arXiv:2608.30874v1 Announce Type: cross Abstract: This paper considers decentralized contingency MPC for multi-agent control under a state-only information pattern, with particular focus on limited se

safetyarxiv-cs-ro

Proximity3D: Shape from Capacitive Proximity on Sensing Manifold

arXiv:2608.30344v1 Announce Type: new Abstract: Most shape reconstruction methods assume measurements defined over planar sensing domains, such as RGB images or depth maps. In this paper, we use a cur

SGM: Safety Glasses for Multimodal Large Language Models via Neuron-Level Detoxification

arXiv:2512.15052v4 Announce Type: replace-cross Abstract: Disclaimer: Samples in this paper may be harmful and cause discomfort. Multimodal large language models (MLLMs) enable multimodal understandin

Simulation-Based Evaluation of Energy-Constrained Quantum-Classical Competition

arXiv:2308.08025v2 Announce Type: replace-cross Abstract: This paper develops a simulation-based framework for evaluating the energy implications of quantum and classical computing firms competing in

researcharxiv-cs-ai

StableWorld: Towards Stable and Consistent Long Interactive Video Generation

arXiv:2601.15281v2 Announce Type: replace Abstract: In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic

SVI2LoD3: Agent-Driven Reconstruction of LoD3 Facade Openings in Semantic 3D City Models from Volunteered Street View Imagery using Large Language and Visual Models

model-releasesarxiv-cs-cv

arXiv:2608.29992v1 Announce Type: new Abstract: This paper presents an end-to-end, agent-driven pipeline for the LoD3 reconstruction of facade openings in 3D city models, producing directly usable Cit

Temporal Analysis of NetFlow Datasets for Network Intrusion Detection Systems

arXiv:2503.04404v3 Announce Type: replace Abstract: This paper investigates the temporal analysis of NetFlow datasets for machine learning (ML)-based network intrusion detection systems (NIDS). Althou

researcharxiv-cs-lg

Toward a Cross-Lingual Romanization Ecosystem for Sinitic Languages: A Paired Mandarin-Cantonese Case Study

arXiv:2608.29170v1 Announce Type: new Abstract: This paper proposes the Sinitic Romanization Ecosystem, a cross-lingual Sinitic romanization design framework with supporting digital infrastructure and

safetyarxiv-cs-cl

Toward Cultural Alignment: Human-Centered Evaluation of Multimodal AI Stories Across Five African Communities

arXiv:2608.29209v1 Announce Type: new Abstract: In this paper, we examine how well AI-generated multimodal stories align with the lived practices, relationships, language, values, and visual expectati

safetyarxiv-cs-cl

A Method for Layer Bit-Width Allocation in LLM Quantization via Performance Maximization Under a Quality-Degradation Constraint

model-releasesarxiv-cs-lg

arXiv:2608.28003v1 Announce Type: new Abstract: This paper proposes a layer bit allocation method for Gemma-3-1B, formulating the problem as performance maximization (latency decrease) given a degrada

GAN-Based Semantic Communication for Image Transmission in IoV

arXiv:2608.27989v1 Announce Type: new Abstract: For cooperative perception in the internet of vehicles, this paper proposes a generative adversarial network-based semantic communication framework to a

safetyarxiv-cs-cv

How Proper Scoring Rules Shape LLM Forecasting

arXiv:2608.28482v1 Announce Type: new Abstract: This paper evaluates how reward function choice shapes the performance and behavior of LLM forecasters. We compare five proper scoring rules as training

Image Augmentation as Test Generation for Deep Learning-Based Image Retrieval Systems

arXiv:2608.27502v1 Announce Type: cross Abstract: Ensuring the reliability of deep learning-based image retrieval systems is a software engineering challenge. This paper presents a dual contribution:

Lexically conditioned realization ambiguity in Korean predicate morphology

arXiv:2608.27966v1 Announce Type: new Abstract: This paper examines Korean surface realization as distinct from morphological analysis. It asks whether a sequence of canonical morphemes and grammatica

researcharxiv-cs-cl

SafeStep: An Interactive Demonstration of Semantic Communication for Pedestrian Safety Monitoring

arXiv:2608.27688v1 Announce Type: new Abstract: In this paper, we develop SafeStep, an interactive browser-based semantic communication platform for live pedestrian safety monitoring. SafeStep extract

Visual Token Coding for Video Multimodal Large Language Models

arXiv:2608.28008v1 Announce Type: new Abstract: In this paper, we propose a new token compression paradigm for video Multimodal Large Language Models (MLLMs), termed Visual Token Coding (VTC). Inspire

What Will This Copper Look Like Later? Forecasting Surface Appearance and Rendering It as a PBR Material

model-releasesarxiv-cs-cv

arXiv:2608.28102v1 Announce Type: cross Abstract: Digital design requires predicting how a metal surface will look later in its oxidation; this paper presents such a pipeline for copper. Given a fixed