paper-with-me

Prompt Engineering

16개 벤치마크 · 논문 1,874편 · 이 태스크의 논문 보기 →

Benchmarks

ImageNet

결과 15개

Caltech-101

결과 14개

DTD

결과 14개

EuroSAT

결과 14개

FGVC-Aircraft

결과 14개

Oxford 102 Flower

결과 14개

SUN397

결과 14개

Stanford Cars

결과 14개

UCF101

결과 14개

Food-101

결과 13개

ImageNet-A

결과 9개

ImageNet-R

결과 9개

ImageNet-S

결과 9개

ImageNet V2

결과 8개

ImageNet-21k

결과 2개

Most implemented

GPT Understands, Too

2021-03-18 · 구현 10개

Visual Prompt Tuning

2022-03-23 · 구현 6개

Papers

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

2026-09-09 · Jonathan A. Handler, Marlene I. Robles-Granda, Jacob E. Mefford, Jeremy S. McGarvey 외 arxiv

Background: Emergency Department (ED) return visits are commonly reviewed for quality assurance, but are often limited (e.g., to revisits within 48-72 hours) to increase actionable finding yield while minimizing chart re…

Prompt Engineering

Unifying Conformal Language Tasks with In-Context Ensembles

2026-09-02 · Xiao Shi Huang, Chen-Yuan Lin, Bruce Kuwahara, Kin Kwan Leung 외 hf

Many NLP tasks, such as summarization and extractive question answering, reduce to retrieving relevant content from documents under two constraints: coverage, retaining enough pertinent information to achieve some goal, …

Question AnsweringPrompt Engineering

Stratified Consistency Distillation for Natural Language Formalization

2026-08-31 · Zhichao Hou, Ferhat Erata, Joe Lilien, MohamadAli Torkamani arxiv

Neurosymbolic reasoning has shown promising success in addressing complex reasoning tasks by combining large language models (LLMs) and symbolic solvers. While this approach shows promise, a fundamental challenge remains…

Prompt Engineering

The Differential Reasoning Router: Operationalizing Cost-Aware LLM Annotation in E-commerce

2026-08-31 · Cheng Lyu, Jingyue Zhang, Vinny DeGenova, Mengwei Li 외 arxiv

Large Language Models (LLMs) are increasingly used to annotate structured product data in e-commerce, but early deployment often begins as a cold-start problem: only limited pre-launch labels are available, the value of …

Prompt Engineering

Thomson: Continual Learning of Frontier Models for SovereignAI

2026-08-27 · Shengzhuang Chen, Jerrod Parker, Yejin Bang, Andrew M. Bean 외 arxiv

The development of frontier models is commonly perceived to be the exclusive remit of a small number of heavily funded players, creating an information, economic and power asymmetry between developers and the diverse use…

Continual LearningPrompt EngineeringDomain Adaptation

CRAMER: Control via Request-Aware Masking for Editing Recommenders

2026-08-26 · Zhiyuan Julian Su, Naihe Feng, Zhen Luther Qin, Ga Wu arxiv

Sequential recommendation models, while powerful, have limited flexibility in responding to immediate user requests, making it difficult to adapt their recommendations to the user's timely interests. Unfortunately, exist…

Sequential RecommendationPrompt Engineering

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