Scholar
Jinglong Gao
Google Scholar ID: jaVvkHIAAAAJ
Harbin Institute of Technology
Citations & Impact
Citations
138
H-index
4
i10-index
2
Publications
10
Co-authors
6
list available
Publications
Resume (English only)
Academic Achievements
- - Publications:
- * Master-O1: Towards Proficient Slow Thinking for O1-like Reasoning.
- * CrossICL: Cross-Task In-Context Learning via Unsupervised Demonstration Transfer.
- * ExpeTrans: LLMs Are Experiential Transfer Learners.
- * Com$^2$: A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models.
- * Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection.
- * Enhancing Complex Causality Extraction via Improved Subtask Interaction and Knowledge Fusion.
- * Event Causality Identification via Competitive-Cooperative Cognition Networks.
- * Self-Evolving GPT: A Lifelong Autonomous Experiential Learner.
- * Towards Generalizable and Faithful Logic Reasoning over Natural Language via Resolution Refutation.
- * Is chatgpt a good causal reasoner? a comprehensive evaluation.
- * Discrimloss: A universal loss for hard samples and incorrect samples discrimination.
- - Awards:
- * NLPCC 2024 Outstanding Paper Reward
- * First-Class Graduate Academic Scholarship 2021
- * First-Class People’s Scholarship 2016/2017/2018
Research Experience
- - 2021.10 - 2022.12, Huawei Cloud, China. AI Algorithm Engineer.
- - 2023.11 - 2024.03, iFLYTEK Research, Beijing, China. Agent Algorithm Engineer.
Education
- - 2016.09 - 2020.06, Harbin Institute of Technology, China. Bachelor of Engineering, Computer Science.
- - 2020.09 - 2021.06, Harbin Institute of Technology, China. Master of Engineering, Computer Science. Advisor: Prof. Ting Liu.
- - 2021.09 - Present, Harbin Institute of Technology, China. Ph.D. Candidate. Advisors: Prof. Ting Liu and Prof. Xiao Ding.
Background
- - Research Interests: Causal reasoning, intelligent agents (self-evolution, transfer, and generalization), and slow thinking for large language models (LLMs)
- - Advisors: Prof. Ting Liu and Prof. Xiao Ding
