Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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On the Brittleness of CLIP Text Encoders

NVIDIA Nemotron Nano V2 VL

Improving Diagnostic Performance on Small and Imbalanced Datasets Using Class-Based Input Image Composition

Retrofitters, pragmatists and activists: Public interest litigation for accountable automated decision-making

Text to Robotic Assembly of Multi Component Objects using 3D Generative AI and Vision Language Models

The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Project

AURA: A Reinforcement Learning Framework for AI-Driven Adaptive Conversational Surveys

Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs

USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencoding

CompressionAttack: Exploiting Prompt Compression as a New Attack Surface in LLM-Powered Agents

Every Activation Boosted: Scaling General Reasoner to 1 Trillion Open Language Foundation

Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics

What Can String Probability Tell Us About Grammaticality?

Fine-Tuning MedGemma for Clinical Captioning to Enhance Multimodal RAG over Malaysia CPGs

Learning to Navigate Socially Through Proactive Risk Perception

Policy-as-Prompt: Turning AI Governance Rules into Guardrails for AI Agents

A Mega-Study of Digital Twins Reveals Strengths, Weaknesses and Opportunities for Further Improvement

Amortized Latent Steering: Low-Cost Alternative to Test-Time Optimization

Amulet: a Python Library for Assessing Interactions Among ML Defenses and Risks

LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence

AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning

What Matters in Data for DPO?

Chain-of-Query: Unleashing the Power of LLMs in SQL-Aided Table Understanding via Multi-Agent Collaboration

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving

Advanced Hybrid Transformer LSTM Technique with Attention and TS Mixer for Drilling Rate of Penetration Prediction

Learning Dynamics of Meta-Learning in Small Model Pretraining

GAITEX: Human motion dataset of impaired gait and rehabilitation exercises using inertial and optical sensors

To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks

NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Finance

ZERO: Industry-ready Vision Foundation Model with Multi-modal Prompts

Conformal Information Pursuit for Interactively Guiding Large Language Models

Less Greedy Equivalence Search

Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities

Know What You Don't Know: Uncertainty Calibration of Process Reward Models

Conformal Prediction Adaptive to Unknown Subpopulation Shifts

ProRefine: Inference-Time Prompt Refinement with Textual Feedback

Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme

RCCDA: Adaptive Model Updates in the Presence of Concept Drift under a Constrained Resource Budget

Optimizing Anytime Reasoning via Budget Relative Policy Optimization

Taskmaster Deconstructed: A Quantitative Look at Tension, Volatility, and Viewer Ratings

XBreaking: Understanding how LLMs security alignment can be broken

Pogobot: an Open-Source, Low-Cost Robot for Swarm Robotics and Programmable Active Matter

Large language models as uncertainty-calibrated optimizers for experimental discovery

AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science

InterFeedback: Unveiling Interactive Intelligence of Large Multimodal Models via Human Feedback

Analyzing limits for in-context learning

Activation-Informed Merging of Large Language Models

iTool: Reinforced Fine-Tuning with Dynamic Deficiency Calibration for Advanced Tool Use

MMDocIR: Benchmarking Multimodal Retrieval for Long Documents

Cognitive Edge Computing: A Comprehensive Survey on Optimizing Large Models and AI Agents for Pervasive Deployment

TOBUGraph: Knowledge Graph-Based Retrieval for Enhanced LLM Performance Beyond RAG

CTPD: Cross-Modal Temporal Pattern Discovery for Enhanced Multimodal Electronic Health Records Analysis

Affordance-based Robot Manipulation with Flow Matching

FunOTTA: On-the-Fly Adaptation on Cross-Domain Fundus Image via Stable Test-time Training

Tactical Decision Making for Autonomous Trucks by Deep Reinforcement Learning with Total Cost of Operation Based Reward

Characterizing the Training Dynamics of Private Fine-tuning with Langevin diffusion

Learning for Interval Prediction of Electricity Demand: A Cluster-based Bootstrapping Approach

The Less Intelligent the Elements, the More Intelligent the Whole. Or, Possibly Not?

Monitor-Generate-Verify (MGV): Formalising Metacognitive Theory for Language Model Reasoning

Outbidding and Outbluffing Elite Humans: Mastering Liar's Poker via Self-Play and Reinforcement Learning

A Proprietary Model-Based Safety Response Framework for AI Agents

Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning

Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base

From Observability Data to Diagnosis: An Evolving Multi-agent System for Incident Management in Cloud Systems

How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations

String Seed of Thought: Prompting LLMs for Distribution-Faithful and Diverse Generation

HugAgent: Benchmarking LLMs for Simulation of Individualized Human Reasoning

Internal World Models as Imagination Networks in Cognitive Agents

Open Agent Specification (Agent Spec): A Unified Representation for AI Agents

Bilinear relational structure fixes reversal curse and enables consistent model editing

Introducing LongCat-Flash-Thinking: A Technical Report

AI Through the Human Lens: Investigating Cognitive Theories in Machine Psychology

Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search

Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization

Joint Verification and Refinement of Language Models for Safety-Constrained Planning

TimeSearch-R: Adaptive Temporal Search for Long-Form Video Understanding via Self-Verification Reinforcement Learning

DGTN: Graph-Enhanced Transformer with Diffusive Attention Gating Mechanism for Enzyme DDG Prediction

On Flow Matching KL Divergence

AI Literacy Assessment Revisited: A Task-Oriented Approach Aligned with Real-world Occupations

SWE-Compass: Towards Unified Evaluation of Agentic Coding Abilities for Large Language Models

Self-adaptive weighting and sampling for physics-informed neural networks

APP: Accelerated Path Patching with Task-Specific Pruning

"I Like That You Have to Poke Around": Instructors on How Experiential Approaches to AI Literacy Spark Inquiry and Critical Thinking

ProDER: A Continual Learning Approach for Fault Prediction in Evolving Smart Grids

Multi-modal Loop Closure Detection with Foundation Models in Severely Unstructured Environments

Robust Neural Audio Fingerprinting using Music Foundation Models

Sample Complexity of Distributionally Robust Off-Dynamics Reinforcement Learning with Online Interaction

AI Assisted AR Assembly: Object Recognition and Computer Vision for Augmented Reality Assisted Assembly

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework

AI Literacy for Community Colleges: Instructors' Perspectives on Scenario-Based and Interactive Approaches to Teaching AI

A multimodal multiplex of the mental lexicon for multilingual individuals

Perceptually Aligning Representations of Music via Noise-Augmented Autoencoders

What Are the Facts? Automated Extraction of Court-Established Facts from Criminal-Court Opinions

Rethinking Metrics and Diffusion Architecture for 3D Point Cloud Generation

LiveStar: Live Streaming Assistant for Real-World Online Video Understanding

DeepEyesV2: Toward Agentic Multimodal Model

TAMAS: Benchmarking Adversarial Risks in Multi-Agent LLM Systems

Integrating Score-Based Diffusion Models with Machine Learning-Enhanced Localization for Advanced Data Assimilation in Geological Carbon Storage

"i am a stochastic parrot, and so r u": Is AI-based framing of human behaviour and cognition a conceptual metaphor or conceptual engineering?

Created by

Haebom

저자

Warmhold Jan Thomas Mollema, Thomas Wachter

개요

본 논문은 AI 기술의 일상생활 통합 증가에 따라 AI 시스템을 인간 행동 및 인지 능력(예: 언어 습득)과 비유적으로 비교하는 데 AI 관련 개념이 사용되는 현상을 다룬다. 논문은 '계산적' 및 '생물학적' 옹호론의 상반된 입장을 배경으로, 계산 및 AI의 개념적 구조를 인간 영역에 적용할 수 있는지, 그리고 그 의미는 무엇인지 질문한다. Wittgenstein의 개념과 언어 사용에 대한 관점을 바탕으로, 이러한 비교가 개념적 은유인지 또는 개념적 공학 시도인지 두 가지 가능성을 제시하고 비교 분석한다. 논문은 이것이 개념적 은유라고 주장하지만, 이러한 관점이 (1) 자신의 인식론적 우연성을 인식하지 못하고, (2) '지도-영토 오류'를 범할 위험이 있으며, (3) 인간 심리와 계산 간의 은유적 연결 때문에 오해의 소지가 있는 '이중 은유'임을 지적한다. 마지막으로, AI의 인간 영역 투영과 관련된 결점에 대한 대안으로 개념적 은유의 관점이 개념적 공학의 형태에 대한 방향을 제시한다고 주장하며, 이러한 방법론의 기준이 충족되면 개념적 은유 관점과 관련된 오류 및 인식론적 결점을 우회할 수 있다고 결론짓는다. 궁극적으로 인간과 AI 개념 영역의 상호 교류는 현재 개념의 경계가 우리에게 어떻게 작용하고 어떻게 개선될 수 있는지에 대한 새로운 성찰을 촉구한다.

시사점, 한계점

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시사점: 인간과 AI 개념 영역의 상호 교류를 통해 기존 개념의 한계를 재고하고 개선할 수 있는 가능성을 제시한다. 개념적 은유의 분석을 통해 개념적 공학의 새로운 접근법을 모색할 수 있다.

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한계점: 개념적 은유 접근 방식의 인식론적 우연성과 지도-영토 오류의 가능성을 충분히 해결하지 못할 수 있다. 인간 심리와 계산 간의 이중 은유 문제에 대한 명확한 해결책을 제시하지 못한다. 개념적 공학의 기준 설정에 대한 구체적인 설명이 부족하다.

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