Li, Junyi

Incentivizing Dual Process Thinking for Efficient Large Language Model Reasoning

Large reasoning models (LRMs) have demonstrated strong performance on complex reasoning tasks, but often suffer from overthinking, generating redundant content regardless of task difficulty....

SkillHarm: Lifecycle-Aware Skill-Based Attacks via Automated Construction

Entropy-Guided Token Dropout: Training Autoregressive Language Models with Limited Domain Data

SEAR: Self-Judging Agentic Reward Models

YNU-junyi in BioNLP-OST 2019: Using CNN-LSTM Model with Embeddings for SeeDev Binary Event Extraction

Lijunyi at SemEval-2019 Task 9: An attention-based LSTM and ensemble of different models for suggestion mining from online reviews and forums

CLUE: A Chinese Language Understanding Evaluation Benchmark

Lee at SemEval-2020 Task 12: A BERT Model Based on the Maximum Self-ensemble Strategy for Identifying Offensive Language

Lee at SemEval-2020 Task 5: ALBERT Model Based on the Maximum Ensemble Strategy and Different Data Sampling Methods for Detecting Counterfactual Statements

Lijunyi at SemEval-2020 Task 4: An ALBERT Model Based Maximum Ensemble with Different Training Sizes and Depths for Commonsense Validation and Explanation

TextBox: A Unified, Modularized, and Extensible Framework for Text Generation

Few-shot Knowledge Graph-to-Text Generation with Pretrained Language Models

Context-Tuning: Learning Contextualized Prompts for Natural Language Generation

TextBox 2.0: A Text Generation Library with Pre-trained Language Models

ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text Generation

ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models

Learning to Transfer Prompts for Text Generation

Learning to Imagine: Visually-Augmented Natural Language Generation