Cover Image

Understanding In-Context Learning from Repetitions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yan, Jianhao, Xu, Jin, Song, Chiyu, Wu, Chenming, Li, Yafu, Zhang, Yue
Format:	Preprint
Published:	2023
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Potential and Challenges of Model Editing for Social Debiasing
by: Yan, Jianhao, et al.
Published: (2024)

Keys to Robust Edits: from Theoretical Insights to Practical Advances
by: Yan, Jianhao, et al.
Published: (2024)

What Have We Achieved on Non-autoregressive Translation?
by: Li, Yafu, et al.
Published: (2024)

Dynamics of Instruction Fine-Tuning for Chinese Large Language Models
by: Song, Chiyu, et al.
Published: (2023)

Unveiling Attractor Cycles in Large Language Models: A Dynamical Systems View of Successive Paraphrasing
by: Wang, Zhilin, et al.
Published: (2025)

Understanding and Controlling Repetition Neurons and Induction Heads in In-Context Learning
by: Doan, Nhi Hoai, et al.
Published: (2025)

ELICIT: LLM Augmentation via External In-Context Capability
by: Wang, Futing, et al.
Published: (2024)

Learning to Reason under Off-Policy Guidance
by: Yan, Jianhao, et al.
Published: (2025)

Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency Maps
by: Liu, Fuxiao, et al.
Published: (2023)

RefuteBench 2.0 -- Agentic Benchmark for Dynamic Evaluation of LLM Responses to Refutation Instruction
by: Yan, Jianhao, et al.
Published: (2025)

Think Longer to Explore Deeper: Learn to Explore In-Context via Length-Incentivized Reinforcement Learning
by: Wang, Futing, et al.
Published: (2026)

Theoretical Understanding of In-Context Learning in Shallow Transformers with Unstructured Data
by: Xing, Yue, et al.
Published: (2024)

RefuteBench: Evaluating Refuting Instruction-Following for Large Language Models
by: Yan, Jianhao, et al.
Published: (2024)

LexMatcher: Dictionary-centric Data Collection for LLM-based Machine Translation
by: Yin, Yongjing, et al.
Published: (2024)

Lost in the Passage: Passage-level In-context Learning Does Not Necessarily Need a "Passage"
by: Sun, Hao, et al.
Published: (2025)

Unleashing Multi-Hop Reasoning Potential in Large Language Models through Repetition of Misordered Context
by: Yu, Sangwon, et al.
Published: (2024)

GPT-4 vs. Human Translators: A Comprehensive Evaluation of Translation Quality Across Languages, Domains, and Expertise Levels
by: Yan, Jianhao, et al.
Published: (2024)

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning
by: Luo, Yun, et al.
Published: (2023)

Detecting RLVR Training Data via Structural Convergence of Reasoning
by: Zhang, Hongbo, et al.
Published: (2026)

HICL: Hashtag-Driven In-Context Learning for Social Media Natural Language Understanding
by: Tan, Hanzhuo, et al.
Published: (2023)

Repetition Neurons: How Do Language Models Produce Repetitions?
by: Hiraoka, Tatsuya, et al.
Published: (2024)

Evaluating the Capability of Large-scale Language Models on Chinese Grammatical Error Correction Task
by: Qu, Fanyi, et al.
Published: (2023)

Ungrammatical-syntax-based In-context Example Selection for Grammatical Error Correction
by: Tang, Chenming, et al.
Published: (2024)

SCOI: Syntax-augmented Coverage-based In-context Example Selection for Machine Translation
by: Tang, Chenming, et al.
Published: (2024)

Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation
by: Tang, Chenming, et al.
Published: (2024)

Benchmarking GPT-4 against Human Translators: A Comprehensive Evaluation Across Languages, Domains, and Expertise Levels
by: Yan, Jianhao, et al.
Published: (2024)

Spotting AI's Touch: Identifying LLM-Paraphrased Spans in Text
by: Li, Yafu, et al.
Published: (2024)

Identifying Semantic Induction Heads to Understand In-Context Learning
by: Ren, Jie, et al.
Published: (2024)

Conditional Language Learning with Context
by: Zhang, Xiao, et al.
Published: (2024)

Lost in Literalism: How Supervised Training Shapes Translationese in LLMs
by: Li, Yafu, et al.
Published: (2025)

Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification
by: Liu, Shang, et al.
Published: (2024)

FaithRL: Learning to Reason Faithfully through Step-Level Faithfulness Maximization
by: Gui, Runquan, et al.
Published: (2026)

LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
by: Wu, Minghao, et al.
Published: (2023)

Timeline-based Sentence Decomposition with In-Context Learning for Temporal Fact Extraction
by: Chen, Jianhao, et al.
Published: (2024)

Test-Time Preference Optimization: On-the-Fly Alignment via Iterative Textual Feedback
by: Li, Yafu, et al.
Published: (2025)

Deep Literature Survey Automation with an Iterative Workflow
by: Zhang, Hongbo, et al.
Published: (2025)

Feature-Adaptive and Data-Scalable In-Context Learning
by: Li, Jiahao, et al.
Published: (2024)

Shortcut Learning in In-Context Learning: A Survey
by: Song, Rui, et al.
Published: (2024)

Large Language Models Might Not Care What You Are Saying: Prompt Format Beats Descriptions
by: Tang, Chenming, et al.
Published: (2024)

MAGE: Machine-generated Text Detection in the Wild
by: Li, Yafu, et al.
Published: (2023)