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Does AI See like Art Historians? Interpreting How Vision Language Models Recognize Artistic Style

ViroGym: Realistic Large-Scale Benchmarks for Evaluating Viral Proteins

How to Model AI Agents as Personas?: Applying the Persona Ecosystem Playground to 41,300 Posts on Moltbook for Behavioral Insights

3D aperture-engineered diffractive neural networks for super-resolution electromagnetic wave computing

DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model

A Geometric Analysis of Small-sized Language Model Hallucinations

Language Model Memory and Memory Models for Language

How does longer temporal context enhance multimodal narrative video processing in the brain?

Learning Rate Matters: Vanilla LoRA May Suffice for LLM Fine-tuning

Protein Autoregressive Modeling via Multiscale Structure Generation

Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design

Enabling Real-Time Colonoscopic Polyp Segmentation on Commodity CPUs via Ultra-Lightweight Architecture

WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling

Whispers of Wealth: Red-Teaming Google's Agent Payments Protocol via Prompt Injection

SuperInfer: SLO-Aware Rotary Scheduling and Memory Management for LLM Inference on Superchips

FreeOrbit4D: Training-Free Arbitrary Camera Redirection for Monocular Videos via Foreground-Complete 4D Reconstruction

Disentangling generalization and memorization in large language models using chess

Multimodal system for skin cancer detection

Q-learning with Adjoint Matching

STAGE: A Full-Screenplay Benchmark for Reasoning over Evolving Storie

Tracing Moral Foundations in Large Language Models

Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance

Toward Training Superintelligent Software Agents through Self-Play SWE-RL

MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution

NORi: An ML-Augmented Ocean Boundary Layer Parameterization

Open-Set Domain Adaptation Under Background Distribution Shift: Challenges and A Provably Efficient Solution

HarmonicAttack: An Adaptive Cross-Domain Audio Watermark Removal

Data-driven Acceleration of MPC with Guarantees

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models

PlantTraitNet: An Uncertainty-Aware Multimodal Framework for Global-Scale Plant Trait Inference from Citizen Science Data

Noise-corrected GRPO: From Noisy Rewards to Unbiased Gradients

Needles in the Landscape: Semi-Supervised Pseudolabeling for Archaeological Site Discovery under Label Scarcity

Dr.LLM: Dynamic Layer Routing in LLMs

WARC-Bench: Web Archive Based Benchmark for GUI Subtask Executions

Proximal Diffusion Neural Sampler

Beyond Majority Voting: LLM Aggregation by Leveraging Higher-Order Information

HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling

Jailbreaking on Text-to-Video Models via Scene Splitting Strategy

YAC: Bridging Natural Language and Interactive Visual Exploration with Generative AI for Biomedical Data Discovery

ORCA: An Agentic Reasoning Framework for Hallucination and Adversarial Robustness in Vision-Language Models

Digital Voices of Survival: From Social Media Disclosures to Support Provisions for Domestic Violence Victims

PiKV: KV Cache Management System for Mixture of Experts

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

Fine-tuning Large Language Model for Automated Algorithm Design

Mechanistic Interpretability Needs Philosophy

Recursive Entropic Risk Optimization in Discounted MDPs: Sample Complexity Bounds with a Generative Model

Spatial-MLLM: Boosting MLLM Capabilities in Visual-based Spatial Intelligence

Quantifying the Generalization Gap in Seizure Detection: A Large-Scale Empirical Benchmark via the SzCORE Challenge

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM

GraphPINE: Graph Importance Propagation for Interpretable Drug Response Prediction

Adaptive Camera Sensor for Vision Models

Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews

Deep Neural Network for Musical Instrument Recognition using MFCCs

Latent Action Reparameterization for Efficient Agent Inference

Memory-Guided Tree Search with Cross-Branch Knowledge Transfer for LLM Solver Synthesis

The Capability Paradox: How Smarter Auditors Make Multi-Agent Systems Less Secure

CBT-Audio: Evaluating Audio Language Models for Patient-Side Distress Intensity Estimation in CBT Session Recordings

Recall Isn't Enough: Bounding Commitments in Personalized Language Systems

Skim: Speculative Execution for Fast and Efficient Web Agents

Learning Bilevel Policies over Symbolic World Models for Long-Horizon Planning

ALSO: Adversarial Online Strategy Optimization for Social Agents

$\pi$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows

ChromaFlow: A Negative Ablation Study of Orchestration Overhead in Tool-Augmented Agent Evaluation

Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning

VERA-MH: Validation of Ethical and Responsible AI in Mental Health

TMAS: Scaling Test-Time Compute via Multi-Agent Synergy

Active Testing of Large Language Models via Approximate Neyman Allocation

When to Re-Commit: Temporal Abstraction Discovery for Long-Horizon Vision-Language Reasoning

2.5-D Decomposition for LLM-Based Spatial Construction

Autogenesis: A Self-Evolving Agent Protocol

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold

Contrastive Reasoning Alignment: Reinforcement Learning from Hidden Representations

A Hybrid Modeling Framework for Crop Prediction Tasks via Dynamic Parameter Calibration and Multi-Task Learning

Governing Evolving Memory in LLM Agents: Risks, Mechanisms, and the Stability and Safety Governed Memory (SSGM) Framework

The World Won't Stay Still: Programmable Evolution for Agent Benchmarks

Phase-Aware Mixture of Experts for Agentic Reinforcement Learning

Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases

TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents

Nonlinearity as Rank: Generative Low-Rank Adapter with Radial Basis Functions

High-quality generation of dynamic game content via small language models: A proof of concept

Distributional AGI Safety

BuildArena: A Physics-Aligned Interactive Benchmark of LLMs for Engineering Construction

From Refusal to Recovery: A Control-Theoretic Approach to Generative AI Guardrails

ARM: Discovering Agentic Reasoning Modules for Generalizable Multi-Agent Systems

Learning Efficient Guardrails for Compliance

Extreme Self-Preference in Language Models

Artificial Phantasia: Emergent Mental Imagery in Large Language Models

IR-Agent: Expert-Inspired LLM Agents for Structure Elucidation from Infrared Spectra

Artificial Intelligence, conceptual metaphors and conceptual engineering: Are AI-based framings of human behaviour and cognition successful?

Entry-level guide to the use of large language models for medical research

Atoms of Thought: Universal EEG Representation Learning with Microstates

Long-term Power Grid Planning via Answer Set Programming

Rethinking Visual Attribution for Chest X-ray Reasoning in Large Vision Language Models

Less Back-and-Forth: A Comparative Study of Structured Prompting

Beyond Prediction Accuracy: Target-Space Recovery Profiles for Evaluating Model-Brain Alignment

Toto 2.0: Time Series Forecasting Enters the Scaling Era

k-Inductive Neural Barrier Certificates for Unknown Nonlinear Dynamics

Beyond Isotropy in JEPAs: Hamiltonian Geometry and Symplectic Prediction

Draft Less, Retrieve More: Hybrid Tree Construction for Speculative Decoding

Enhancing News Recommendation with Hierarchical LLM Prompting

Created by

Haebom

저자

Hai-Dang Kieu, Delvin Ce Zhang, Minh Duc Nguyen, Min Xu, Qiang Wu, Dung D. Le

개요

본 논문은 사용자의 뉴스 추천 시스템에서 사용자 선호도의 복잡성을 효과적으로 포착하지 못하는 한계를 극복하기 위해, 대규모 언어 모델(LLM)을 활용한 새로운 방법인 PNR-LLM을 제안합니다. PNR-LLM은 LLM의 생성 능력을 활용하여 뉴스 제목과 초록을 풍부하게 만들고, 이를 통해 추천의 질을 향상시킵니다. 핵심 모듈인 "News Enrichment via LLMs"는 기사로부터 심층적인 의미 정보와 관련 엔티티를 생성하여, 기존의 단순한 정보를 더 풍부한 표현으로 변환합니다. 또한, 강화된 의미 및 엔티티 수준의 데이터를 집계하기 위한 어텐션 메커니즘을 제안하여, 사용자와 뉴스 간의 정확한 매칭을 보여주는 통합된 사용자 및 뉴스 임베딩을 형성합니다. MIND 데이터셋을 사용한 실험 결과, PNR-LLM은 최첨단 기준 모델들을 능가하는 성능을 보였으며, 제안된 데이터 강화 모듈은 모델에 독립적임을 확인하고 여러 기존 모델에 적용하여 성능 향상을 입증했습니다.