Saved in:
| Main Authors: | Sun, Qiushi, Han, Chengcheng, Chen, Nuo, Zhu, Renyu, Gong, Jingyang, Li, Xiang, Gao, Ming |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2305.08088 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Structure-aware Fine-tuning for Code Pre-trained Models
by: Wu, Jiayi, et al.
Published: (2024)
by: Wu, Jiayi, et al.
Published: (2024)
Boosting Language Models Reasoning with Chain-of-Knowledge Prompting
by: Wang, Jianing, et al.
Published: (2023)
by: Wang, Jianing, et al.
Published: (2023)
Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs
by: Li, Zhuo, et al.
Published: (2024)
by: Li, Zhuo, et al.
Published: (2024)
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models
by: Wu, Jiaqi, et al.
Published: (2024)
by: Wu, Jiaqi, et al.
Published: (2024)
Does It Make Sense to Explain a Black Box With Another Black Box?
by: Delaunay, Julien, et al.
Published: (2024)
by: Delaunay, Julien, et al.
Published: (2024)
What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective
by: Han, Guangzeng, et al.
Published: (2026)
by: Han, Guangzeng, et al.
Published: (2026)
A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond
by: Sun, Qiushi, et al.
Published: (2024)
by: Sun, Qiushi, et al.
Published: (2024)
Selective Prompting Tuning for Personalized Conversations with LLMs
by: Huang, Qiushi, et al.
Published: (2024)
by: Huang, Qiushi, et al.
Published: (2024)
TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills
by: Sun, Qiushi, et al.
Published: (2023)
by: Sun, Qiushi, et al.
Published: (2023)
Selection of LLM Fine-Tuning Data based on Orthogonal Rules
by: Li, Xiaomin, et al.
Published: (2024)
by: Li, Xiaomin, et al.
Published: (2024)
Jailbreaking Commercial Black-Box LLMs with Explicitly Harmful Prompts
by: Zhang, Chiyu, et al.
Published: (2025)
by: Zhang, Chiyu, et al.
Published: (2025)
CrossTune: Black-Box Few-Shot Classification with Label Enhancement
by: Luo, Danqing, et al.
Published: (2024)
by: Luo, Danqing, et al.
Published: (2024)
Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration
by: Xu, Ran, et al.
Published: (2025)
by: Xu, Ran, et al.
Published: (2025)
Evaluating the Effectiveness of Black-Box Prompt Optimization as the Scale of LLMs Continues to Grow
by: Zhou, Ziyu, et al.
Published: (2025)
by: Zhou, Ziyu, et al.
Published: (2025)
Deep Learning-based Method for Expressing Knowledge Boundary of Black-Box LLM
by: Sheng, Haotian, et al.
Published: (2026)
by: Sheng, Haotian, et al.
Published: (2026)
Black-box Prompt Tuning with Subspace Learning
by: Zheng, Yuanhang, et al.
Published: (2023)
by: Zheng, Yuanhang, et al.
Published: (2023)
Vbox: Efficient Black-Box Serializability Verification
by: Sun, Weihua, et al.
Published: (2025)
by: Sun, Weihua, et al.
Published: (2025)
Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis
by: Yu, Jianxiang, et al.
Published: (2024)
by: Yu, Jianxiang, et al.
Published: (2024)
Black-Box Prompt Optimization: Aligning Large Language Models without Model Training
by: Cheng, Jiale, et al.
Published: (2023)
by: Cheng, Jiale, et al.
Published: (2023)
Decoding the Black Box: Discerning AI Rhetorics About and Through Poetic Prompting
by: Edgar, P. D., et al.
Published: (2025)
by: Edgar, P. D., et al.
Published: (2025)
Inference-Aware Prompt Optimization for Aligning Black-Box Large Language Models
by: Mahmud, Saaduddin, et al.
Published: (2025)
by: Mahmud, Saaduddin, et al.
Published: (2025)
PSM: Prompt Sensitivity Minimization via LLM-Guided Black-Box Optimization
by: Jawad, Huseein, et al.
Published: (2025)
by: Jawad, Huseein, et al.
Published: (2025)
Incremental Context-free Grammar Inference in Black Box Settings
by: Li, Feifei, et al.
Published: (2024)
by: Li, Feifei, et al.
Published: (2024)
Auto-Tuning Safety Guardrails for Black-Box Large Language Models
by: Abdulkadir, Perry
Published: (2025)
by: Abdulkadir, Perry
Published: (2025)
Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning
by: Zhang, Mingtian, et al.
Published: (2024)
by: Zhang, Mingtian, et al.
Published: (2024)
Consistency Matters: Explore LLMs Consistency From a Black-Box Perspective
by: Zhao, Fufangchen, et al.
Published: (2024)
by: Zhao, Fufangchen, et al.
Published: (2024)
Knowledge Distillation of Black-Box Large Language Models
by: Chen, Hongzhan, et al.
Published: (2024)
by: Chen, Hongzhan, et al.
Published: (2024)
JanusCoder: Towards a Foundational Visual-Programmatic Interface for Code Intelligence
by: Sun, Qiushi, et al.
Published: (2025)
by: Sun, Qiushi, et al.
Published: (2025)
WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation
by: Zheng, Zinan, et al.
Published: (2026)
by: Zheng, Zinan, et al.
Published: (2026)
Beyond Black-Box Interventions: Latent Probing for Faithful Retrieval-Augmented Generation
by: Gao, Linfeng, et al.
Published: (2025)
by: Gao, Linfeng, et al.
Published: (2025)
Plug and Play with Prompts: A Prompt Tuning Approach for Controlling Text Generation
by: Ajwani, Rohan Deepak, et al.
Published: (2024)
by: Ajwani, Rohan Deepak, et al.
Published: (2024)
TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification
by: Gubri, Martin, et al.
Published: (2024)
by: Gubri, Martin, et al.
Published: (2024)
APrompt4EM: Augmented Prompt Tuning for Generalized Entity Matching
by: Xia, Yikuan, et al.
Published: (2024)
by: Xia, Yikuan, et al.
Published: (2024)
Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning
by: Zhu, Jiapeng, et al.
Published: (2026)
by: Zhu, Jiapeng, et al.
Published: (2026)
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment
by: Wang, Jianing, et al.
Published: (2024)
by: Wang, Jianing, et al.
Published: (2024)
Boosting Text-To-Image Generation via Multilingual Prompting in Large Multimodal Models
by: Mu, Yongyu, et al.
Published: (2025)
by: Mu, Yongyu, et al.
Published: (2025)
UMB@PerAnsSumm 2025: Enhancing Perspective-Aware Summarization with Prompt Optimization and Supervised Fine-Tuning
by: Qi, Kristin, et al.
Published: (2025)
by: Qi, Kristin, et al.
Published: (2025)
Learning From Correctness Without Prompting Makes LLM Efficient Reasoner
by: Yao, Yuxuan, et al.
Published: (2024)
by: Yao, Yuxuan, et al.
Published: (2024)
Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMs
by: Le, Chenqian, et al.
Published: (2025)
by: Le, Chenqian, et al.
Published: (2025)
From Parameters to Prompts: Understanding and Mitigating the Factuality Gap between Fine-Tuned LLMs
by: Gong, Xuan, et al.
Published: (2025)
by: Gong, Xuan, et al.
Published: (2025)
Similar Items
-
Structure-aware Fine-tuning for Code Pre-trained Models
by: Wu, Jiayi, et al.
Published: (2024) -
Boosting Language Models Reasoning with Chain-of-Knowledge Prompting
by: Wang, Jianing, et al.
Published: (2023) -
Self-Instructed Derived Prompt Generation Meets In-Context Learning: Unlocking New Potential of Black-Box LLMs
by: Li, Zhuo, et al.
Published: (2024) -
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models
by: Wu, Jiaqi, et al.
Published: (2024) -
Does It Make Sense to Explain a Black Box With Another Black Box?
by: Delaunay, Julien, et al.
Published: (2024)