14 citations · 18 across the 26 of their papers we have counts for
6 papers · 1 filter
TinyHelen's First Curriculum: Training and Evaluating Tiny Language Models in a Simpler Language Environment
Ke Yang, Volodymyr Kindratenko, ChengXiang Zhai
Training language models (LMs) and their application agents is increasingly costly due to large datasets and models, making test failures difficult to bear. Simplified language env…
ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study
Eric Modesitt, Ke Yang, Spencer Hulsey +2
Recent advances in language modeling demonstrate the need for high-quality domain-specific training data, especially for tasks that require specialized knowledge. General-purpose m…
AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents
Ke Yang, Yao Liu, Sapana Chaudhary +4
Autonomy via agents using large language models (LLMs) for personalized, standardized tasks boosts human efficiency. Automating web tasks (like booking hotels within a budget) is i…
Bias and Volatility: A Statistical Framework for Evaluating Large Language Model's Stereotypes and the Associated Generation Inconsistency
Yiran Liu, Ke Yang, Zehan Qi +3
We present a novel statistical framework for analyzing stereotypes in large language models (LLMs) by systematically estimating the bias and variation in their generation. Current…
Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement
Chenkai Sun, Ke Yang, Revanth Gangi Reddy +5
The increasing demand for personalized interactions with large language models (LLMs) calls for methodologies capable of accurately and efficiently identifying user opinions and pr…
If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents
Ke Yang, Jiateng Liu, John Wu +9
The prominent large language models (LLMs) of today differ from past language models not only in size, but also in the fact that they are trained on a combination of natural langua…