Saved in:
| Main Authors: | Liu, Jiayi, Yang, Tinghan, Neville, Jennifer |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.14833 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
by: Schnabel, Tobias, et al.
Published: (2024)
by: Schnabel, Tobias, et al.
Published: (2024)
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation
by: Zhang, Jiaxing, et al.
Published: (2024)
by: Zhang, Jiaxing, et al.
Published: (2024)
BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching
by: Zheng, Zhen, et al.
Published: (2024)
by: Zheng, Zhen, et al.
Published: (2024)
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
by: Wang, Zhexuan, et al.
Published: (2026)
by: Wang, Zhexuan, et al.
Published: (2026)
Selection-p: Self-Supervised Task-Agnostic Prompt Compression for Faithfulness and Transferability
by: Chung, Tsz Ting, et al.
Published: (2024)
by: Chung, Tsz Ting, et al.
Published: (2024)
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
by: Zhou, Han, et al.
Published: (2023)
by: Zhou, Han, et al.
Published: (2023)
Self-Supervised Prompt Optimization
by: Xiang, Jinyu, et al.
Published: (2025)
by: Xiang, Jinyu, et al.
Published: (2025)
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots
by: Herlihy, Christine, et al.
Published: (2024)
by: Herlihy, Christine, et al.
Published: (2024)
Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models
by: Li, Miao, et al.
Published: (2026)
by: Li, Miao, et al.
Published: (2026)
FaithLM: Towards Faithful Explanations for Large Language Models
by: Chuang, Yu-Neng, et al.
Published: (2024)
by: Chuang, Yu-Neng, et al.
Published: (2024)
Faithfulness Evaluation for Decoder-only LLM Attributions with Controlled Retained Information
by: Huang, Xin, et al.
Published: (2026)
by: Huang, Xin, et al.
Published: (2026)
Task Facet Learning: A Structured Approach to Prompt Optimization
by: Juneja, Gurusha, et al.
Published: (2024)
by: Juneja, Gurusha, et al.
Published: (2024)
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
Utility-Diversity Aware Online Batch Selection for LLM Supervised Fine-tuning
by: Zou, Heming, et al.
Published: (2025)
by: Zou, Heming, et al.
Published: (2025)
Batched Contextual Reinforcement: A Task-Scaling Law for Efficient Reasoning
by: Yang, Bangji, et al.
Published: (2026)
by: Yang, Bangji, et al.
Published: (2026)
Automatic Prompt Optimization with Prompt Distillation
by: Dyagin, Ernest A., et al.
Published: (2025)
by: Dyagin, Ernest A., et al.
Published: (2025)
Investigating the Interplay between Contextual and Parametric Chain-of-Thought Faithfulness under Optimization
by: Sun, Jingyi, et al.
Published: (2026)
by: Sun, Jingyi, et al.
Published: (2026)
Simulating Students or Sycophantic Problem Solving? On Misconception Faithfulness of LLM Simulators
by: Do, Heejin, et al.
Published: (2026)
by: Do, Heejin, et al.
Published: (2026)
Power Lines: Scaling Laws for Weight Decay and Batch Size in LLM Pre-training
by: Bergsma, Shane, et al.
Published: (2025)
by: Bergsma, Shane, et al.
Published: (2025)
Prompt-Response Semantic Divergence Metrics for Faithfulness Hallucination and Misalignment Detection in Large Language Models
by: Halperin, Igor
Published: (2025)
by: Halperin, Igor
Published: (2025)
DynaPrompt: Dynamic Test-Time Prompt Tuning
by: Xiao, Zehao, et al.
Published: (2025)
by: Xiao, Zehao, et al.
Published: (2025)
Measuring Faithfulness Depends on How You Measure: Classifier Sensitivity in LLM Chain-of-Thought Evaluation
by: Young, Richard J.
Published: (2026)
by: Young, Richard J.
Published: (2026)
StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization
by: Tang, Yiming, et al.
Published: (2025)
by: Tang, Yiming, et al.
Published: (2025)
Local Prompt Optimization
by: Jain, Yash, et al.
Published: (2025)
by: Jain, Yash, et al.
Published: (2025)
ChameleonLLM: Batch-Aware Dynamic Low-Rank Adaptation via Inference-Time Clusters
by: Yuksel, Kamer Ali, et al.
Published: (2025)
by: Yuksel, Kamer Ali, et al.
Published: (2025)
FaithfulSAE: Towards Capturing Faithful Features with Sparse Autoencoders without External Dataset Dependencies
by: Cho, Seonglae, et al.
Published: (2025)
by: Cho, Seonglae, et al.
Published: (2025)
Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers
by: Zhao, Andrew, et al.
Published: (2025)
by: Zhao, Andrew, et al.
Published: (2025)
PromptWizard: Task-Aware Prompt Optimization Framework
by: Agarwal, Eshaan, et al.
Published: (2024)
by: Agarwal, Eshaan, et al.
Published: (2024)
Efficient Prompt Optimization Through the Lens of Best Arm Identification
by: Shi, Chengshuai, et al.
Published: (2024)
by: Shi, Chengshuai, et al.
Published: (2024)
EfficientLLM: Efficiency in Large Language Models
by: Yuan, Zhengqing, et al.
Published: (2025)
by: Yuan, Zhengqing, et al.
Published: (2025)
FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"
by: Ming, Yifei, et al.
Published: (2024)
by: Ming, Yifei, et al.
Published: (2024)
Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference
by: Adamska, Marta, et al.
Published: (2025)
by: Adamska, Marta, et al.
Published: (2025)
Prompt Optimization Via Diffusion Language Models
by: Wang, Shiyu, et al.
Published: (2026)
by: Wang, Shiyu, et al.
Published: (2026)
Transformer Circuit Faithfulness Metrics are not Robust
by: Miller, Joseph, et al.
Published: (2024)
by: Miller, Joseph, et al.
Published: (2024)
A Data-Centric Approach To Generate Faithful and High Quality Patient Summaries with Large Language Models
by: Hegselmann, Stefan, et al.
Published: (2024)
by: Hegselmann, Stefan, et al.
Published: (2024)
Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts
by: Yin, Yueqin, et al.
Published: (2024)
by: Yin, Yueqin, et al.
Published: (2024)
No Prompt Left Behind: Exploiting Zero-Variance Prompts in LLM Reinforcement Learning via Entropy-Guided Advantage Shaping
by: Le, Thanh-Long V., et al.
Published: (2025)
by: Le, Thanh-Long V., et al.
Published: (2025)
Joint Detection of Fraud and Concept Drift inOnline Conversations with LLM-Assisted Judgment
by: Senol, Ali, et al.
Published: (2025)
by: Senol, Ali, et al.
Published: (2025)
DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection
by: Yu, Xiao, et al.
Published: (2023)
by: Yu, Xiao, et al.
Published: (2023)
Incorporating Attribution Importance for Improving Faithfulness Metrics
by: Zhao, Zhixue, et al.
Published: (2023)
by: Zhao, Zhixue, et al.
Published: (2023)
Similar Items
-
Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
by: Schnabel, Tobias, et al.
Published: (2024) -
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation
by: Zhang, Jiaxing, et al.
Published: (2024) -
BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching
by: Zheng, Zhen, et al.
Published: (2024) -
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
by: Wang, Zhexuan, et al.
Published: (2026) -
Selection-p: Self-Supervised Task-Agnostic Prompt Compression for Faithfulness and Transferability
by: Chung, Tsz Ting, et al.
Published: (2024)