Prompt Engineering

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

16 leaderboard tables shown for this task, 16 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 16 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

16 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 454 papers with code (1,236 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Learning Transferable Visual Models From Natural Language Supervision
  26 Feb 2021 82 repositories listed Syntology ran 16 of 20 samples · 4 unverified · 16 pointer-only (licence)
  State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories.
• Learning to Prompt for Vision-Language Models
  2 Sep 2021 18 repositories listed Syntology ran 3 of 12 samples · 9 unverified
  Large pre-trained vision-language models like CLIP have shown great potential in learning representations that are transferable across a wide range of downstream tasks.
• Conditional Prompt Learning for Vision-Language Models
  10 Mar 2022 12 repositories listed Syntology ran 4 of 6 samples · 2 unverified
  With the rise of powerful pre-trained vision-language models like CLIP, it becomes essential to investigate ways to adapt these models to downstream datasets.
• GPT Understands, Too
  18 Mar 2021 10 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 2 pointer-only (licence)
  Prompting a pretrained language model with natural language patterns has been proved effective for natural language understanding (NLU).
• Multitask Prompted Training Enables Zero-Shot Task Generalization
  15 Oct 2021 8 repositories listed Syntology ran 8 of 15 samples · 7 unverified
  Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020).
• Visual Prompt Tuning
  23 Mar 2022 6 repositories listed Syntology ran 17 of 27 samples · 10 unverified · 15 pointer-only (licence)
  The current modus operandi in adapting pre-trained models involves updating all the backbone parameters, ie, full fine-tuning.
• GPT Takes the Bar Exam
  29 Dec 2022 5 repositories listed
  Nearly all jurisdictions in the United States require a professional license exam, commonly referred to as "the Bar Exam," as a precondition for law practice.
• Large Language Models Are Human-Level Prompt Engineers
  3 Nov 2022 5 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  By conditioning on natural language instructions, large language models (LLMs) have displayed impressive capabilities as general-purpose computers.
• LangGPT: Rethinking Structured Reusable Prompt Design Framework for LLMs from the Programming Language
  26 Feb 2024 4 repositories listed
  Experiments illustrate that LangGPT significantly enhances the performance of LLMs.
• IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
  13 Aug 2023 4 repositories listed Syntology ran 3 of 8 samples · 5 unverified
  Despite the simplicity of our method, an IP-Adapter with only 22M parameters can achieve comparable or even better performance to a fully fine-tuned image prompt model.
• MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
  23 Jun 2023 4 repositories listed
  Multimodal Large Language Model (MLLM) relies on the powerful LLM to perform multimodal tasks, showing amazing emergent abilities in recent studies, such as writing poems based on an image.
• Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
  30 Aug 2021 4 repositories listed Syntology ran 3 of 4 samples · 1 unverified
  Large-scale pre-trained language models have contributed significantly to natural language processing by demonstrating remarkable abilities as few-shot learners.
• The Prompt Report: A Systematic Survey of Prompting Techniques
  6 Jun 2024 3 repositories listed Syntology ran 3 of 5 samples · 2 unverified
  Generative Artificial Intelligence (GenAI) systems are increasingly being deployed across diverse industries and research domains.
• Chain-of-Thought Reasoning Without Prompting
  15 Feb 2024 3 repositories listed
  Our findings reveal that, intriguingly, CoT reasoning paths can be elicited from pre-trained LLMs by simply altering the \textit{decoding} process.
• Optimizing Prompts for Text-to-Image Generation
  19 Dec 2022 3 repositories listed Syntology ran 1 of 9 samples · 8 unverified
  Instead of laborious human engineering, we propose prompt adaptation, a general framework that automatically adapts original user input to model-preferred prompts.
• MaPLe: Multi-modal Prompt Learning
  6 Oct 2022 3 repositories listed Syntology ran 4 of 6 samples · 2 unverified
  Pre-trained vision-language (V-L) models such as CLIP have shown excellent generalization ability to downstream tasks.
• Ask Me Anything: A simple strategy for prompting language models
  5 Oct 2022 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Prompting is a brittle process wherein small modifications to the prompt can cause large variations in the model predictions, and therefore significant effort is dedicated towards designing a painstakingly "perfect…
• CLIP-Adapter: Better Vision-Language Models with Feature Adapters
  9 Oct 2021 3 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Large-scale contrastive vision-language pre-training has shown significant progress in visual representation learning.
• Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs
  12 Jun 2025 2 repositories listed
  Particularly, we design a fine-grained multi-objective reward specifically for time series forecasting, and then introduce GRIP (group-based relative importance for policy optimization), which leverages non-uniform…
• From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios
  4 Feb 2025 2 repositories listed
  Ensuring the safety of autonomous vehicles requires virtual scenario-based testing, which depends on the robust evaluation and generation of safety-critical scenarios.
• A Comparison of Prompt Engineering Techniques for Task Planning and Execution in Service Robotics
  30 Oct 2024 2 repositories listed
  Recent advances in LLM have been instrumental in autonomous robot control and human-robot interaction by leveraging their vast general knowledge and capabilities to understand and reason across a wide range of tasks and…
• HPT++: Hierarchically Prompting Vision-Language Models with Multi-Granularity Knowledge Generation and Improved Structure Modeling
  27 Aug 2024 2 repositories listed
  Specifically, we introduce a relationship-guided attention module to capture pair-wise associations among entities and attributes for low-level prompt learning.
• LAPT: Label-driven Automated Prompt Tuning for OOD Detection with Vision-Language Models
  12 Jul 2024 2 repositories listed Syntology ran 8 of 17 samples · 9 unverified
  The LAPT framework operates autonomously, requiring only ID class names as input and eliminating the need for manual intervention.
• Paraphrase Types Elicit Prompt Engineering Capabilities
  28 Jun 2024 2 repositories listed
  In particular, changes in morphology and lexicon, i.
• Understanding Sounds, Missing the Questions: The Challenge of Object Hallucination in Large Audio-Language Models
  12 Jun 2024 2 repositories listed
  Large audio-language models (LALMs) enhance traditional large language models by integrating audio perception capabilities, allowing them to tackle audio-related tasks.
• On the Worst Prompt Performance of Large Language Models
  8 Jun 2024 2 repositories listed
  To address these limitations, we introduce RobustAlpacaEval, a new benchmark that consists of semantically equivalent case-level queries and emphasizes the importance of using the worst prompt performance to gauge the…
• Optimizing Large Language Models for OpenAPI Code Completion
  24 May 2024 2 repositories listed
  This study evaluates the OpenAPI completion performance of GitHub Copilot, a prevalent commercial code completion tool, and proposes a set of task-specific optimizations leveraging Meta's open-source model Code Llama.
• Can We Use Large Language Models to Fill Relevance Judgment Holes?
  9 May 2024 2 repositories listed
  Incomplete relevance judgments limit the re-usability of test collections.
• Semantic Routing for Enhanced Performance of LLM-Assisted Intent-Based 5G Core Network Management and Orchestration
  24 Apr 2024 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Large language models (LLMs) are rapidly emerging in Artificial Intelligence (AI) applications, especially in the fields of natural language processing and generative AI.
• PRISM: A Promptable and Robust Interactive Segmentation Model with Visual Prompts
  23 Apr 2024 2 repositories listed
  (3) Corrective learning.

Syntology lines on 16 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.