Why is prompting hard? Understanding prompts on binary sequence predictors
Fuente:
arXiv
Saved in:
| Main Authors: | Wenliang, Li Kevin, Ruoss, Anian, Grau-Moya, Jordi, Hutter, Marcus, Genewein, Tim |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Understanding Prompt Tuning and In-Context Learning via Meta-Learning
by: Genewein, Tim, et al.
Published: (2025)
by: Genewein, Tim, et al.
Published: (2025)
Language Modeling Is Compression
by: Delétang, Grégoire, et al.
Published: (2023)
by: Delétang, Grégoire, et al.
Published: (2023)
Learning Universal Predictors
by: Grau-Moya, Jordi, et al.
Published: (2024)
by: Grau-Moya, Jordi, et al.
Published: (2024)
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
by: Heurtel-Depeiges, David, et al.
Published: (2024)
by: Heurtel-Depeiges, David, et al.
Published: (2024)
Amortized Planning with Large-Scale Transformers: A Case Study on Chess
by: Ruoss, Anian, et al.
Published: (2024)
by: Ruoss, Anian, et al.
Published: (2024)
LMAct: A Benchmark for In-Context Imitation Learning with Long Multimodal Demonstrations
by: Ruoss, Anian, et al.
Published: (2024)
by: Ruoss, Anian, et al.
Published: (2024)
Distributional Bellman Operators over Mean Embeddings
by: Wenliang, Li Kevin, et al.
Published: (2023)
by: Wenliang, Li Kevin, et al.
Published: (2023)
Dynamic Embeddings with Task-Oriented prompting
by: Balloccu, Allmin, et al.
Published: (2024)
by: Balloccu, Allmin, et al.
Published: (2024)
Efficient multi-prompt evaluation of LLMs
by: Polo, Felipe Maia, et al.
Published: (2024)
by: Polo, Felipe Maia, et al.
Published: (2024)
Evil twins are not that evil: Qualitative insights into machine-generated prompts
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2024)
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2024)
Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation
by: Dong, Harry, et al.
Published: (2024)
by: Dong, Harry, et al.
Published: (2024)
Soft-prompt Tuning for Large Language Models to Evaluate Bias
by: Tian, Jacob-Junqi, et al.
Published: (2023)
by: Tian, Jacob-Junqi, et al.
Published: (2023)
Do different prompting methods yield a common task representation in language models?
by: Davidson, Guy, et al.
Published: (2025)
by: Davidson, Guy, et al.
Published: (2025)
Exploring prompts to elicit memorization in masked language model-based named entity recognition
by: Xia, Yuxi, et al.
Published: (2024)
by: Xia, Yuxi, et al.
Published: (2024)
Reverse Stable Diffusion: What prompt was used to generate this image?
by: Croitoru, Florinel-Alin, et al.
Published: (2023)
by: Croitoru, Florinel-Alin, et al.
Published: (2023)
GreenTEA: Gradient Descent with Topic-modeling and Evolutionary Auto-prompting
by: Dong, Zheng, et al.
Published: (2025)
by: Dong, Zheng, et al.
Published: (2025)
Intent-based Prompt Calibration: Enhancing prompt optimization with synthetic boundary cases
by: Levi, Elad, et al.
Published: (2024)
by: Levi, Elad, et al.
Published: (2024)
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models
by: Fu, Shuai, et al.
Published: (2024)
by: Fu, Shuai, et al.
Published: (2024)
StateAct: Enhancing LLM Base Agents via Self-prompting and State-tracking
by: Rozanov, Nikolai, et al.
Published: (2024)
by: Rozanov, Nikolai, et al.
Published: (2024)
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
by: Fu, Wenjie, et al.
Published: (2023)
by: Fu, Wenjie, et al.
Published: (2023)
DAIC-WOZ: On the Validity of Using the Therapist's prompts in Automatic Depression Detection from Clinical Interviews
by: Burdisso, Sergio, et al.
Published: (2024)
by: Burdisso, Sergio, et al.
Published: (2024)
Illuminate: A novel approach for depression detection with explainable analysis and proactive therapy using prompt engineering
by: Agrawal, Aryan
Published: (2024)
by: Agrawal, Aryan
Published: (2024)
Your Policy Regularizer is Secretly an Adversary
by: Brekelmans, Rob, et al.
Published: (2022)
by: Brekelmans, Rob, et al.
Published: (2022)
L3Cube-MahaEmotions: A Marathi Emotion Recognition Dataset with Synthetic Annotations using CoTR prompting and Large Language Models
by: Kowtal, Nidhi, et al.
Published: (2025)
by: Kowtal, Nidhi, et al.
Published: (2025)
Partition Tree Weighting for Non-Stationary Stochastic Bandits
by: Veness, Joel, et al.
Published: (2025)
by: Veness, Joel, et al.
Published: (2025)
Introducing HALC: A general pipeline for finding optimal prompting strategies for automated coding with LLMs in the computational social sciences
by: Reich, Andreas, et al.
Published: (2025)
by: Reich, Andreas, et al.
Published: (2025)
Language hooks: a modular framework for augmenting LLM reasoning that decouples tool usage from the model and its prompt
by: de Mijolla, Damien, et al.
Published: (2024)
by: de Mijolla, Damien, et al.
Published: (2024)
The meaning of prompts and the prompts of meaning: Semiotic reflections and modelling
by: Thellefsen, Martin, et al.
Published: (2025)
by: Thellefsen, Martin, et al.
Published: (2025)
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
by: Sclar, Melanie, et al.
Published: (2023)
by: Sclar, Melanie, et al.
Published: (2023)
PII-Compass: Guiding LLM training data extraction prompts towards the target PII via grounding
by: Nakka, Krishna Kanth, et al.
Published: (2024)
by: Nakka, Krishna Kanth, et al.
Published: (2024)
Ask, and it shall be given: On the Turing completeness of prompting
by: Qiu, Ruizhong, et al.
Published: (2024)
by: Qiu, Ruizhong, et al.
Published: (2024)
Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance
by: Aiyappa, Rachith, et al.
Published: (2024)
by: Aiyappa, Rachith, et al.
Published: (2024)
What's in a prompt? Language models encode literary style in prompt embeddings
by: Sarfati, Raphaël, et al.
Published: (2025)
by: Sarfati, Raphaël, et al.
Published: (2025)
Visual prompting reimagined: The power of the Activation Prompts
by: Zhang, Yihua, et al.
Published: (2026)
by: Zhang, Yihua, et al.
Published: (2026)
Transmuting prompts into weights
by: Mazzawi, Hanna, et al.
Published: (2025)
by: Mazzawi, Hanna, et al.
Published: (2025)
Mastering Board Games by External and Internal Planning with Language Models
by: Schultz, John, et al.
Published: (2024)
by: Schultz, John, et al.
Published: (2024)
MRPD: Undersampled MRI reconstruction by prompting a large latent diffusion model
by: Gao, Ziqi, et al.
Published: (2024)
by: Gao, Ziqi, et al.
Published: (2024)
Demystifying optimized prompts in language models
by: Melamed, Rimon, et al.
Published: (2025)
by: Melamed, Rimon, et al.
Published: (2025)
Do prompt positions really matter?
by: Mao, Junyu, et al.
Published: (2023)
by: Mao, Junyu, et al.
Published: (2023)
Emergent misalignment as prompt sensitivity: A research note
by: Wyse, Tim, et al.
Published: (2025)
by: Wyse, Tim, et al.
Published: (2025)
Similar Items
-
Understanding Prompt Tuning and In-Context Learning via Meta-Learning
by: Genewein, Tim, et al.
Published: (2025) -
Language Modeling Is Compression
by: Delétang, Grégoire, et al.
Published: (2023) -
Learning Universal Predictors
by: Grau-Moya, Jordi, et al.
Published: (2024) -
Compression via Pre-trained Transformers: A Study on Byte-Level Multimodal Data
by: Heurtel-Depeiges, David, et al.
Published: (2024) -
Amortized Planning with Large-Scale Transformers: A Case Study on Chess
by: Ruoss, Anian, et al.
Published: (2024)