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Swarm Intelligence Optimization of UAV Routing with Simultaneously Stochastic Pick-up and Delivery during COVID-19

Published in International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), 2023

This paper investigates swarm intelligence optimization for UAV routing during COVID-19.

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Multimodal Stock Price Forecasting Using Attention Mechanism Based on Multi-Task Learning

Published in Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data, 2023

This paper explores multimodal stock price forecasting using attention mechanisms and multi-task learning.

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PRCA: Fitting Black-Box Large Language Models for Retrieval Question Answering via Pluggable Reward-Driven Contextual Adapter

Published in Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023

This paper discusses fitting black-box large language models for retrieval question answering using a pluggable reward-driven contextual adapter.

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Can We Trust LLMs? Mitigate Overconfidence Bias in LLMs through Knowledge Transfer

Published in arXiv preprint arXiv:2405.16856, 2024

This paper discusses mitigating overconfidence bias in large language models through knowledge transfer.

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Exploring Performance Contrasts in TableQA: Step-by-Step Reasoning Boosts Bigger Language Models, Limits Smaller Language Models

Published in arXiv preprint arXiv:2411.16002, 2024

This paper proposes the Table-Logic framework to investigate performance contrasts between large and small language models on the TableQA task using step-by-step reasoning methods.

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PFID: Privacy First Inference Delegation Framework for LLMs

Published in arXiv preprint arXiv:2406.12238, 2024

This paper presents the PFID framework for privacy-first inference delegation in large language models.

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BURExtract-Llama: An LLM for Clinical Concept Extraction in Breast Ultrasound Reports

Published in ACM MM 2024 Workshop MCHM (Oral), 2024

This paper presents BURExtract-Llama, an LLM designed for clinical concept extraction from breast ultrasound reports.

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Dynamic Noise Preference Optimization for LLM Self-Improvement via Synthetic Data

Published in Under Review by ICLR 2025, 2024

This paper introduces Dynamic Noise Preference Optimization (DNPO) for self-improvement in large language models via synthetic data.

Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.

NYU Langone Health

Remote, March 2024 - Present

Research Assistant (NLP for Healthcare Focused), advised by Professor Artie Shen.

Ping An Technology

Shenzhen, March 2023 - June 2023

Algorithm Engineer Intern (NLP Focused), advised by Senior Algorithm Engineer Zhitao Li.

SF Express

Shanghai, August 2021 - September 2021

Data Analyst Intern

Samsung Research America

Mountain View, May 2024 - August 2024

Researcher Intern (LLMs Focused), advised by Research Scientist Ting Hua and co-advised by Professor Shangqian Gao.

Tongcheng Travel

Suzhou, June 2021 - July 2021

Data Analyst Intern