Emine Yılmaz

Overview of the TREC 2019 deep learning track

2020 · arXiv (Cornell University)

The Deep Learning Track is a new track for TREC 2019, with the goal of studying ad hoc ranking in a large data regime. It is the first track with large human-labeled training sets, introducing …

Overview of the TREC 2021 deep learning track

2025 · arXiv (Cornell University)

This is the fifth year of the TREC Deep Learning track. As in previous years, we leverage the MS MARCO datasets that made hundreds of thousands of human-annotated training labels available for both passage and …

MetaASSIST: Robust Dialogue State Tracking with Meta Learning

2022

Existing dialogue datasets contain lots of noise in their state annotations. Such noise can hurt model training and ultimately lead to poor generalization performance. A general framework named ASSIST has recently been proposed to train …

Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentation

2023 · arXiv (Cornell University)

Conversational Recommendation System (CRS) is a rapidly growing research area that has gained significant attention alongside advancements in language modelling techniques. However, the current state of conversational recommendation faces numerous challenges due to its relative …

Understanding the Role of User Profile in the Personalization of Large Language Models

2024 · arXiv (Cornell University)

Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to enhance the performance on a wide range of tasks. However, the precise role of user profiles and their effect mechanism on LLMs …