Papers by Jiashi Feng

2 papers
LV-BERT: Exploiting Layer Variety for BERT (2021.findings-acl)

Copied to clipboard

Challenge: Modern pre-trained language models are mostly built upon stereotyped development sets . LV-BERT model obtained by our method outperforms BERT on various downstream tasks .
Approach: They propose to exploit layer variety from the layer type set and the layer order to improve pre-trained models.
Outcome: The proposed model outperforms BERT and its variants on various downstream tasks.
MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration (2024.emnlp-main)

Copied to clipboard

Challenge: Large language models (LLMs) have advanced natural language processing, demonstrating exceptional reasoning, tool usage, and memory capabilities.
Approach: They propose a competition-based benchmark framework specifically designed to assess LLMs within multi-agent environments.
Outcome: The proposed framework enhances the LLMs’ abilities in navigating complex social and cognitive dimensions by over threefold between the strongest and weakest LLM models.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations