"prompt engineering" Papers
15 papers found
Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?
Egor Zverev, Sahar Abdelnabi, Soroush Tabesh et al.
ICLR 2025posterarXiv:2403.06833
45
citations
Difference Inversion: Interpolate and Isolate the Difference with Token Consistency for Image Analogy Generation
Hyunsoo Kim, Donghyun Kim, Suhyun Kim
CVPR 2025posterarXiv:2506.07750
1
citations
No Loss, No Gain: Gated Refinement and Adaptive Compression for Prompt Optimization
Wenhang Shi, Yiren Chen, Shuqing Bian et al.
NeurIPS 2025posterarXiv:2509.23387
Quantifying Elicitation of Latent Capabilities in Language Models
Elizabeth Donoway, Hailey Joren, Arushi Somani et al.
NeurIPS 2025poster
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations
Kailas Vodrahalli, James Zou
ICML 2024poster
COMMA: Co-articulated Multi-Modal Learning
Authors: Lianyu Hu, Liqing Gao, Zekang Liu et al.
AAAI 2024paperarXiv:2401.00268
GPTSwarm: Language Agents as Optimizable Graphs
Mingchen Zhuge, Wenyi Wang, Louis Kirsch et al.
ICML 2024poster
Improving Knowledge Extraction from LLMs for Task Learning through Agent Analysis
James Kirk, Robert Wray, Peter Lindes et al.
AAAI 2024paperarXiv:2306.06770
7
citations
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
ICML 2024poster
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
Lichang Chen, Jiuhai Chen, Tom Goldstein et al.
ICML 2024poster
LLMGA: Multimodal Large Language Model based Generation Assistant
Bin Xia, Shiyin Wang, Yingfan Tao et al.
ECCV 2024posterarXiv:2311.16500
25
citations
Position: Towards Implicit Prompt For Text-To-Image Models
Yue Yang, Yuqi Lin, Hong Liu et al.
ICML 2024poster
Prompt-Based Distribution Alignment for Unsupervised Domain Adaptation
Shuanghao Bai, Min Zhang, Wanqi Zhou et al.
AAAI 2024paperarXiv:2312.09553
82
citations
Text-to-Image Generation for Abstract Concepts
Jiayi Liao, Xu Chen, Qiang Fu et al.
AAAI 2024paperarXiv:2309.14623
21
citations
Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
ICML 2024poster