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πŸ€– AI Agent12 items

Latest AI agent research papers, analysis, and improvement insights

semantic_scholarresearch

AgentDrift: A Step-Labeled Benchmark of Injection-Hijacked LLM Agent Trajectories

LLM μ—μ΄μ „νŠΈμ˜ κ°„μ ‘ ν”„λ‘¬ν”„νŠΈ μ£Όμž… 곡격을 λ‹¨κ³„λ³„λ‘œ μΈ‘μ •ν•˜λŠ” 벀치마크

semantic_scholarresearch

BenchShield: Formal Model-Backed Instrumentation for Reward Integrity in LLM-Agent Evaluation Infrastructure

μ—μ΄μ „νŠΈ λ²€μΉ˜λ§ˆν¬μ—μ„œ 보상 해킹을 λ°©μ§€ν•˜λŠ” ν˜•μ‹ λͺ¨λΈ 기반 평가 인프라

semantic_scholarresearch

AgentLeak: Cloning Stronger LLM Agent Capabilities onto Weaker Agents Beyond Skill Stealing

λΈ”λž™λ°•μŠ€ μƒν˜Έμž‘μš©μœΌλ‘œ κ°•λ ₯ν•œ μ—μ΄μ „νŠΈμ˜ 암묡적 지식을 μ•½ν•œ μ—μ΄μ „νŠΈλ‘œ 이전

semantic_scholarresearch

AURA-Eval: Evaluation Framework for Acting Under Risk Awareness in LLM Agent Trajectories

μ•ˆμ „ν•œ μ˜μ‚¬κ²°μ •κ³Ό μœ„ν—˜ 인식을 μ„ΈλΆ„ν™”ν•˜μ—¬ ν‰κ°€ν•˜λŠ” μ—μ΄μ „νŠΈ μ•ˆμ „μ„± ν”„λ ˆμž„μ›Œν¬

semantic_scholarresearch

What Does an LLM-Agent Leaderboard Rank Actually Compare?

μ—μ΄μ „νŠΈ λ¦¬λ”λ³΄λ“œ 점수의 톡계적 타당성과 비ꡐ 쑰건 뢄석

semantic_scholarresearch

Personalizing LLM Agent Memory Using Biometrics

μ‚¬μš©μž 신원 인증 기반 λ©€ν‹°μ‚¬μš©μž ν™˜κ²½μ—μ„œ κ°œμΈν™”λœ μ—μ΄μ „νŠΈ λ©”λͺ¨λ¦¬ 관리

semantic_scholarresearch

Agentic Share-of-Search: A Multi-Agent AI System for Competitive Decision-Making in LLM-Mediated E-Commerce

λ©€ν‹°μ—μ΄μ „νŠΈλ‘œ AI μ‡Όν•‘ κ²½ν—˜μ—μ„œ 판맀자의 경쟁λ ₯κ³Ό κ°€μ‹œμ„±μ„ λΆ„μ„Β·μ΅œμ ν™”

semantic_scholarresearch

Robust Conformal Consensus: Multi-Agent LLM-as-a-Judge Interval Evaluation with Conformal Prediction

μ—¬λŸ¬ LLM μ—μ΄μ „νŠΈ νŒμ‚¬μ˜ 평가 결과에 λŒ€ν•œ λΆˆν™•μ‹€μ„±μ„ μ •λŸ‰ν™”ν•˜λŠ” 방법

semantic_scholarresearch

A Layered Analysis of Disagreement And Answer Quality in Multi-Agent LLM Debate

λ©€ν‹°μ—μ΄μ „νŠΈ 토둠이 μ‹€μ œ 의견 λΆˆμΌμΉ˜μ™€ λ‹΅λ³€ κ°œμ„ μ„ μ΄λ£¨λŠ”μ§€ 싀증 뢄석

semantic_scholarresearch

An LLM-based multi-agent framework for automated reliability analysis of spatially variable soils

ν† μ–‘ 곡학 λ„λ©”μΈμ˜ μžλ™ν™”λœ μ‹ λ’°μ„± 뢄석을 μˆ˜ν–‰ν•˜λŠ” λ©€ν‹°μ—μ΄μ „νŠΈ μ‹œμŠ€ν…œ

hackernewsresearch

The worst spam emails: iLands AI agent hustle

AI μ—μ΄μ „νŠΈλ₯Ό μ•…μš©ν•œ λŒ€κ·œλͺ¨ 슀팸 메일 배포 κ΄€λ ¨ λΉ„νŒ 기사

hackernewsresearch

LRU is harder to beat than the KV-cache papers suggest

LLM μ»¨ν…μŠ€νŠΈ μΊμ‹œ μ΅œμ ν™”μ—μ„œ LRU λ©”λͺ¨λ¦¬ 관리 μ•Œκ³ λ¦¬μ¦˜μ˜ νš¨μœ¨μ„± μž¬κ²€μ¦