activity
20192023
most citedGraph Embedding on Biomedical Networks: Methods, Applications, and Evaluations

413 citations · 486 across the 13 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CL2023

Roll Up Your Sleeves: Working with a Collaborative and Engaging Task-Oriented Dialogue System

Lingbo Mo, Shijie Chen, Ziru Chen +10

We introduce TacoBot, a user-centered task-oriented digital assistant designed to guide users through complex real-world tasks with multiple steps. Covering a wide range of cooking…

cs.CL2023★ 10 cited

Reasoning with Language Model is Planning with World Model

Shibo Hao, Yi Gu, Haodi Ma +4

Large language models (LLMs) have shown remarkable reasoning capabilities, especially when prompted to generate intermediate reasoning steps (e.g., Chain-of-Thought, CoT). However,…

cs.CL2023★ 19 cited

ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings

Shibo Hao, Tianyang Liu, Zhen Wang +1

Augmenting large language models (LLMs) with external tools has emerged as a promising approach to solving complex problems. However, traditional methods, which finetune LLMs with…

cs.CL2023★ 1 cited

GPT is becoming a Turing machine: Here are some ways to program it

Ana Jojic, Zhen Wang, Nebojsa Jojic

We demonstrate that, through appropriate prompting, GPT-3 family of models can be triggered to perform iterative behaviours necessary to execute (rather than just write or recall)…

cs.CL2023★ 30 cited

Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning

Zhen Wang, Rameswar Panda, Leonid Karlinsky +3

Prompt tuning, in which a base pretrained model is adapted to each task via conditioning on learned prompt vectors, has emerged as a promising approach for efficiently adapting lar…