5 papers
Beyond Task Completion: Revealing Corrupt Success in LLM Agents through Procedure-Aware Evaluation
Hongliu Cao, Ilias Driouich, Eoin Thomas
Large Language Model (LLM)-based agents are increasingly adopted in high-stakes settings, but current benchmarks evaluate mainly whether a task was completed, not how. We introduce…
Semantic Adapter for Universal Text Embeddings: Diagnosing and Mitigating Negation Blindness to Enhance Universality
Hongliu Cao
Negation plays an important role in various natural language processing tasks such as Natural Language Inference and Sentiment Analysis tasks. Numerous prior studies have found tha…
Holistic analysis on the sustainability of Federated Learning across AI product lifecycle
Hongliu Cao
In light of emerging legal requirements and policies focused on privacy protection, there is a growing trend of companies across various industries adopting Federated Learning (FL)…
Writing Style Matters: An Examination of Bias and Fairness in Information Retrieval Systems
Hongliu Cao
The rapid advancement of Language Model technologies has opened new opportunities, but also introduced new challenges related to bias and fairness. This paper explores the uncharte…
Recent advances in text embedding: A Comprehensive Review of Top-Performing Methods on the MTEB Benchmark
Hongliu Cao
Text embedding methods have become increasingly popular in both industrial and academic fields due to their critical role in a variety of natural language processing tasks. The sig…