:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Xinzhe, Liu, Ming, Gao, Shang
Format:	Preprint
Published:	2023
Subjects:	Computation and Language
Online Access:	https://arxiv.org/abs/2307.00456
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Rendering Data Unlearnable by Exploiting LLM Alignment Mechanisms
by: Zhang, Ruihan, et al.
Published: (2026)

Can Pretrained Language Models Derive Correct Semantics from Corrupt Subwords under Noise?
by: Li, Xinzhe, et al.
Published: (2023)

GRAMMAR: Grounded and Modular Methodology for Assessment of Closed-Domain Retrieval-Augmented Language Model
by: Li, Xinzhe, et al.
Published: (2024)

A Survey on Out-of-Distribution Evaluation of Neural NLP Models
by: Li, Xinzhe, et al.
Published: (2023)

Rethinking ChatGPT's Success: Usability and Cognitive Behaviors Enabled by Auto-regressive LLMs' Prompting
by: Li, Xinzhe, et al.
Published: (2024)

The Unlearnability Phenomenon in RLVR for Language Models
by: Chen, Yulin, et al.
Published: (2026)

Multimodal Foundation Models Exploit Text to Make Medical Image Predictions
by: Buckley, Thomas, et al.
Published: (2023)

Evaluating the Effectiveness of Direct Preference Optimization for Personalizing German Automatic Text Simplifications for Persons with Intellectual Disabilities
by: Gao, Yingqiang, et al.
Published: (2025)

A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning
by: Li, Xinzhe
Published: (2024)

Making Text Embedders Few-Shot Learners
by: Li, Chaofan, et al.
Published: (2024)

Text as a Universal Interface for Transferable Personalization
by: Liu, Yuting, et al.
Published: (2026)

Small Language Model Makes an Effective Long Text Extractor
by: Chen, Yelin, et al.
Published: (2025)

Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification
by: Mou, Guanyi, et al.
Published: (2024)

Exploiting Dialect Identification in Automatic Dialectal Text Normalization
by: Alhafni, Bashar, et al.
Published: (2024)

Learning to Learn for Few-shot Continual Active Learning
by: Ho, Stella, et al.
Published: (2023)

Hint Tuning: Less Data Makes Better Reasoners
by: Fan, Siqi, et al.
Published: (2026)

ProMind-LLM: Proactive Mental Health Care via Causal Reasoning with Sensor Data
by: Zheng, Xinzhe, et al.
Published: (2025)

From Text to Trust: Empowering AI-assisted Decision Making with Adaptive LLM-powered Analysis
by: Li, Zhuoyan, et al.
Published: (2025)

Semantics-Preserved Distortion for Personal Privacy Protection in Information Management
by: Li, Jiajia, et al.
Published: (2022)

Can You Make It Sound Like You? Post-Editing LLM-Generated Text for Personal Style
by: Baumler, Connor, et al.
Published: (2026)

Text Generation Beyond Discrete Token Sampling
by: Zhuang, Yufan, et al.
Published: (2025)

Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning
by: Wang, Jianing, et al.
Published: (2023)

Making LLMs Better Many-to-Many Speech-to-Text Translators with Curriculum Learning
by: Du, Yexing, et al.
Published: (2024)

Shallow Preference Signals: Large Language Model Aligns Even Better with Truncated Data?
by: Qi, Xuan, et al.
Published: (2025)

Towards Effective Model Editing for LLM Personalization
by: Huang, Baixiang, et al.
Published: (2025)

Personalized Text Generation with Contrastive Activation Steering
by: Zhang, Jinghao, et al.
Published: (2025)

Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation
by: Peng, Letian, et al.
Published: (2023)

Unlearnable Examples for Diffusion Models: Protect Data from Unauthorized Exploitation
by: Zhao, Zhengyue, et al.
Published: (2023)

Domain-Hierarchy Adaptation via Chain of Iterative Reasoning for Few-shot Hierarchical Text Classification
by: Ji, Ke, et al.
Published: (2024)

Text2Freq: Learning Series Patterns from Text via Frequency Domain
by: Lo, Ming-Chih, et al.
Published: (2024)

Text-guided Image Restoration and Semantic Enhancement for Text-to-Image Person Retrieval
by: Liu, Delong, et al.
Published: (2023)

Learning to Rewrite Prompts for Personalized Text Generation
by: Li, Cheng, et al.
Published: (2023)

Enhancing Source Code Classification Effectiveness via Prompt Learning Incorporating Knowledge Features
by: Ma, Yong, et al.
Published: (2024)

When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection
by: Gao, Lang, et al.
Published: (2025)

Exploiting Text Semantics for Few and Zero Shot Node Classification on Text-attributed Graph
by: Wang, Yuxiang, et al.
Published: (2025)

ExPerT: Effective and Explainable Evaluation of Personalized Long-Form Text Generation
by: Salemi, Alireza, et al.
Published: (2025)

What Makes Diffusion Language Models Super Data Learners?
by: Gao, Zitian, et al.
Published: (2025)

Exploring the Mystery of Influential Data for Mathematical Reasoning
by: Ni, Xinzhe, et al.
Published: (2024)

An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data
by: Pham, Trinh, et al.
Published: (2026)

Don't Start Over: A Cost-Effective Framework for Migrating Personalized Prompts Between LLMs
by: Zhao, Ziyi, et al.
Published: (2026)