Daily Arxiv

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Sekai: A Video Dataset towards World Exploration

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

One-Step Diffusion for Detail-Rich and Temporally Consistent Video Super-Resolution

Capturing Polysemanticity with PRISM: A Multi-Concept Feature Description Framework

Efficient Retail Video Annotation: A Robust Key Frame Generation Approach for Product and Customer Interaction Analysis

WebXAII: an open-source web framework to study human-XAI interaction

Refining music sample identification with a self-supervised graph neural network

Decoupled Classifier-Free Guidance for Counterfactual Diffusion Models

Essential-Web v1.0: 24T tokens of organized web data

Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models

LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction

Screen Hijack: Visual Poisoning of VLM Agents in Mobile Environments

SP-VLA: A Joint Model Scheduling and Token Pruning Approach for VLA Model Acceleration

Serving Large Language Models on Huawei CloudMatrix384

Machine Learning Methods for Small Data and Upstream Bioprocessing Applications: A Comprehensive Review

Med-U1: Incentivizing Unified Medical Reasoning in LLMs via Large-scale Reinforcement Learning

Two Heads Are Better than One: Simulating Large Transformers with Small Ones

BreastDCEDL: Curating a Comprehensive DCE-MRI Dataset and developing a Transformer Implementation for Breast Cancer Treatment Response Prediction

Semantic Preprocessing for LLM-based Malware Analysis

A Minimalist Method for Fine-tuning Text-to-Image Diffusion Models

Human-like Forgetting Curves in Deep Neural Networks

Convergent Linear Representations of Emergent Misalignment

LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment

TARDIS STRIDE: A Spatio-Temporal Road Image Dataset and World Model for Autonomy

Autonomous Computer Vision Development with Agentic AI

The Memory Paradox: Why Our Brains Need Knowledge in an Age of AI

SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks

Using Language and Road Manuals to Inform Map Reconstruction for Autonomous Driving

Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing

PlantBert: An Open Source Language Model for Plant Science

Info-Coevolution: An Efficient Framework for Data Model Coevolution

SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes

SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code

UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation

KVCache Cache in the Wild: Characterizing and Optimizing KVCache Cache at a Large Cloud Provider

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Towards Efficient Few-shot Graph Neural Architecture Search via Partitioning Gradient Contribution

Optimizing Sensory Neurons: Nonlinear Attention Mechanisms for Accelerated Convergence in Permutation-Invariant Neural Networks for Reinforcement Learning

CryoCCD: Conditional Cycle-consistent Diffusion with Biophysical Modeling for Cryo-EM Synthesis

More Thinking, Less Seeing? Assessing Amplified Hallucination in Multimodal Reasoning Models

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement

Dynamic Risk Assessments for Offensive Cybersecurity Agents

SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation

Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets

Breaking the Compression Ceiling: Data-Free Pipeline for Ultra-Efficient Delta Compression

Representation Learning with Mutual Influence of Modalities for Node Classification in Multi-Modal Heterogeneous Networks

Learning Dynamics in Continual Pre-Training for Large Language Models

Mask-PINNs: Regulating Feature Distributions in Physics-Informed Neural Networks

Assessing Tenstorrent's RISC-V MatMul Acceleration Capabilities

SPIN-ODE: Stiff Physics-Informed Neural ODE for Chemical Reaction Rate Estimation

PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

DeepSelective: Interpretable Prognosis Prediction via Feature Selection and Compression in EHR Data

Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representations

AerialVG: A Challenging Benchmark for Aerial Visual Grounding by Exploring Positional Relations

PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization

TALE: A Tool-Augmented Framework for Reference-Free Evaluation of Large Language Models

Decentralized Collective World Model for Emergent Communication and Coordination

RL2Grid: Benchmarking Reinforcement Learning in Power Grid Operations

Efficient but Vulnerable: Benchmarking and Defending LLM Batch Prompting Attack

LLMs in Disease Diagnosis: A Comparative Study of DeepSeek-R1 and O3 Mini Across Chronic Health Conditions

Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies

QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation

Dynamic Knowledge Integration for Evidence-Driven Counter-Argument Generation with Large Language Models

AlignDistil: Token-Level Language Model Alignment as Adaptive Policy Distillation

Eau De $Q$-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning

Hierarchical and Modular Network on Non-prehensile Manipulation in General Environments

Selective Use of Yannakakis' Algorithm to Improve Query Performance: Machine Learning to the Rescue

FRIDA to the Rescue! Analyzing Synthetic Data Effectiveness in Object-Based Common Sense Reasoning for Disaster Response

Batayan: A Filipino NLP benchmark for evaluating Large Language Models

From RAG to Memory: Non-Parametric Continual Learning for Large Language Models

Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization

ShapeLib: Designing a library of programmatic 3D shape abstractions with Large Language Models

Rethinking Fine-Tuning when Scaling Test-Time Compute: Limiting Confidence Improves Mathematical Reasoning

Guaranteed prediction sets for functional surrogate models

FDLLM: A Dedicated Detector for Black-Box LLMs Fingerprinting

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning

MonoSOWA: Scalable monocular 3D Object detector Without human Annotations

Representation Learning of Point Cloud Upsampling in Global and Local Inputs

Multi-Preference Optimization: Generalizing DPO via Set-Level Contrasts

Incivility and Rigidity: The Risks of Fine-Tuning LLMs for Political Argumentation

Song Form-aware Full-Song Text-to-Lyrics Generation with Multi-Level Granularity Syllable Count Control

Learning Multi-Branch Cooperation for Enhanced Click-Through Rate Prediction at Taobao

On the Limits of Language Generation: Trade-Offs Between Hallucination and Mode Collapse

Web Archives Metadata Generation with GPT-4o: Challenges and Insights

Cyclic Vision-Language Manipulator: Towards Reliable and Fine-Grained Image Interpretation for Automated Report Generation

A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning

Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation

FALCON: Feedback-driven Adaptive Long/short-term memory reinforced Coding Optimization system

Efficient Mixture-of-Expert for Video-based Driver State and Physiological Multi-task Estimation in Conditional Autonomous Driving

ALTA: Compiler-Based Analysis of Transformers

Learning to Route LLMs with Confidence Tokens

Core Knowledge Deficits in Multi-Modal Language Models

AssistantX: An LLM-Powered Proactive Assistant in Collaborative Human-Populated Environment

MaPPER: Multimodal Prior-guided Parameter Efficient Tuning for Referring Expression Comprehension

Can Large Language Models Replace Human Subjects? A Large-Scale Replication of Scenario-Based Experiments in Psychology and Management

LogProber: Disentangling confidence from contamination in LLM responses

V2X-VLM: End-to-End V2X Cooperative Autonomous Driving Through Large Vision-Language Models

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models

Understanding and Reducing the Class-Dependent Effects of Data Augmentation with A Two-Player Game Approach

PromptDSI: Prompt-based Rehearsal-free Instance-wise Incremental Learning for Document Retrieval

A Robot-Assisted Approach to Small Talk Training for Adults with ASD

Created by

Haebom

저자

Rebecca Ramnauth, Dra\v{z}en Br\v{s}\v{c}ic, Brian Scassellati

개요

자폐 스펙트럼 장애(ASD) 성인의 경우 어려움을 겪는 소소한 대화(small talk) 능력 향상을 위한 가정용 자율 로봇 시스템 개발 및 평가 연구이다. 1주간의 연구 결과, ASD 성인들은 로봇 시스템을 통한 훈련을 즐거워했으며, 대화 시작 및 시선 접촉 개선에 상당한 진전을 보였고, 시스템을 대화 능력 향상에 유용한 도구로 인식했다.

시사점, 한계점

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시사점:

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자폐 스펙트럼 장애 성인의 소소한 대화 능력 향상을 위한 새로운 접근법 제시

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가정용 로봇 시스템을 활용한 효과적인 훈련 가능성 확인

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대화 시작 및 시선 접촉과 같은 구체적인 기술 향상 가능성 제시

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ASD 성인의 사회적 통합 및 관계 형성, 직업 기회 확대에 기여 가능성

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한계점:

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참가자 수 및 연구 기간이 제한적임 (1주일간의 연구)

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장기적인 효과 및 일반화 가능성에 대한 추가 연구 필요

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로봇 시스템의 접근성 및 비용 문제 고려 필요

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다양한 ASD 증상 및 중증도를 가진 참가자에 대한 연구 필요

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