[TODO #1] due Saturday Oct 28th

[trigaten]

1. ~Send me~Put these in your short bio (see below) your Github username, email, and Huggingface name
2. Put a short bio in #intros in slack that talks about your experience and what you hope to do on this project.
3. Two options here (choose one) 2a. Perform one of the two unsolved setup goals in https://github.com/trigaten/Prompt_Systematic_Review/issues/1 2b. Read 5 papers in this file and label each as one or more of these categories. Upload your results here. Comment on this issue about which papers you are doing before you start, so you don't overlap with others. No need to read the entire paper, just enough to figure out what it is about.

[kkahadze]

I will do the following:

• Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data
• Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review
• Prompt Engineering, For Students of Medicine and Their Teachers
• A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
• LoGoPrompt: Synthetic Text Images Can Be Good Visual Prompts for Vision-Language Models

[solarwaffles]

I will read and label the following papers:

• "The Creativity of Text-to-Image Generation", http://dx.doi.org/10.1145/3569219.3569352
• "Beyond Traditional Teaching: The Potential of Large Language Models and Chatbots in Graduate Engineering Education", http://dx.doi.org/10.32388/MD04B0
• "Collective Creativity in Crowd Ideation", http://dx.doi.org/10.1145/3411764.3445782
• "Massive prompt cusps: A new signature of warm dark matter", http://dx.doi.org/10.1093/mnrasl/slad043
• "Scientific Literature Text Mining and the Case for Open Access", http://dx.doi.org/10.21428/14888

[hudssntao]

I will do:

1. "Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models",http://arxiv.org/abs/2106.13353v2
2. "Tailored Visions: Enhancing Text-to-Image Generation with Personalized Prompt Rewriting",http://arxiv.org/abs/2310.08129v1
3. "Large Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification",http://arxiv.org/abs/2303.07142v3
4. "Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models",http://arxiv.org/abs/2310.15127v1
5. "Addressing Compiler Errors: Stack Overflow or Large Language Models?",http://arxiv.org/abs/2307.10793v1

[ashay-sriv-06]

1. My hugging face user name is ashay-sriv, email: ashays06@umd.edu.

2. The papers I will be doing are as follows:

a) Review of Large Vision Models and Visual Prompt Engineering, http://arxiv.org/abs/2307.00855v1

b) User-friendly Image Editing with Minimal Text Input: Leveraging Captioning and Injection Techniques",http://arxiv.org/abs/2306.02717v1

c) Structured Chain-of-Thought Prompting for Code Generation,http://arxiv.org/abs/2305.06599v3

d) Optimizing Prompts for Text-to-Image Generation,http://arxiv.org/abs/2212.09611v1

e) "PEACE: Prompt Engineering Automation for CLIPSeg Enhancement in Aerial Robotics",http://arxiv.org/abs/2310.00085v1

f) "Optimizing Mobile-Edge AI-Generated Everything (AIGX) Services by Prompt Engineering: Fundamental, Framework, and Case Study", http://arxiv.org/abs/2309.01065v1

g) "QaNER: Prompting Question Answering Models for Few-shot Named Entity Recognition",http://arxiv.org/abs/2203.01543v2

[sauravv15]

I'm doing: 1) MetaPrompting: Learning to Learn Better Prompts,http://arxiv.org/abs/2209.11486v4 2) "A Case Study in Engineering a Conversational Programming Assistant's Persona",http://arxiv.org/abs/2301.10016v1 3) Towards Zero-Shot and Few-Shot Table Question Answering using GPT-3,http://arxiv.org/abs/2210.17284v1 4) Cheap-fake Detection with LLM using Prompt Engineering,http://arxiv.org/abs/2306.02776v1 5) ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience",http://arxiv.org/abs/2307.01135v1

[vahinpalle]

huggingface: vahinpalle

The articles I will read and label are:

"Jailbreaker: Automated Jailbreak Across Multiple Large Language Model Chatbots",http://arxiv.org/abs/2307.08715v1

"S3: Social-network Simulation System with Large Language Model-Empowered Agents",http://arxiv.org/abs/2307.14984v2

"Evaluating ChatGPT text-mining of clinical records for obesity monitoring",http://arxiv.org/abs/2308.01666v1

"Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations",http://arxiv.org/abs/2210.16637v2

"Mini-DALLE3: Interactive Text to Image by Prompting Large Language Models",http://arxiv.org/abs/2310.07653v2

[AayushGupta16]

huggingface: aayushgupta

The articles I'm working on are

Prompt Learning for Action Recognition,http://arxiv.org/abs/2305.12437v1

"Effective Structured Prompting by Meta-Learning and Representative Verbalizer",http://arxiv.org/abs/2306.00618v1

"Invalid Logic, Equivalent Gains: The Bizarreness of Reasoning in Language Model Prompting",http://arxiv.org/abs/2307.10573v2

"High-Fidelity Lake Extraction via Two-Stage Prompt Enhancement: Establishing a Novel Baseline and Benchmark",http://arxiv.org/abs/2308.08443v1

Structured Prompt Tuning,http://arxiv.org/abs/2205.12309v1