24 citations · 29 across the 11 of their papers we have counts for
11 papers
Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs
Jingzhou Jiang, Yi Yang, Kar Yan Tam
Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We propose Layer-wise Representatio…
FLARE: Task-agnostic embedding model evaluation through a normalization process
Jingzhou Jiang, Yixuan Tang, Yi Yang +1
When task-specific labels are not available, it becomes difficult to select an embedding model for a specific target corpus. Existing labelless measures based on kernel estimators…
Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness
Hanyu Duan, Yi Yang, Ahmed Abbasi +1
Machine unlearning is the process of removing the imprint left by specific data samples during the training of a machine learning model. AI developers, including those building per…
Evaluating and Aligning Human Economic Risk Preferences in LLMs
Jiaxin Liu, Yixuan Tang, Yi Yang +1
Large Language Models (LLMs) are increasingly used in decision-making scenarios that involve risk assessment, yet their alignment with human economic rationality remains unclear. I…
Robust Predictive Modeling Under Unseen Data Distribution Shifts: A Methodological Commentary
Hanyu Duan, Yi Yang, Ahmed Abbasi +1
Most research designing novel predictive models, or employing existing ones, assumes that training and testing data are independent and identically distributed. In practice, the da…
LLM-Measure: Generating Valid, Consistent, and Reproducible Text-Based Measures for Social Science Research
Yi Yang, Hanyu Duan, Jiaxin Liu +1
The increasing use of text as data in social science research necessitates the development of valid, consistent, reproducible, and efficient methods for generating text-based conce…
Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narratives
Jiaxin Liu, Yi Yang, Kar Yan Tam
In this paper, we introduce the Financial-STS task, a financial domain-specific NLP task designed to measure the nuanced semantic similarity between pairs of financial narratives.…
Do LLMs Know about Hallucination? An Empirical Investigation of LLM's Hidden States
Hanyu Duan, Yi Yang, Kar Yan Tam
Large Language Models (LLMs) can make up answers that are not real, and this is known as hallucination. This research aims to see if, how, and to what extent LLMs are aware of hall…
Exploring the Relationship between In-Context Learning and Instruction Tuning
Hanyu Duan, Yixuan Tang, Yi Yang +2
In-Context Learning (ICL) and Instruction Tuning (IT) are two primary paradigms of adopting Large Language Models (LLMs) to downstream applications. However, they are significantly…
Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads
Yi Yang, Hanyu Duan, Ahmed Abbasi +2
Transformer-based pretrained large language models (PLM) such as BERT and GPT have achieved remarkable success in NLP tasks. However, PLMs are prone to encoding stereotypical biase…
InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning
Yi Yang, Yixuan Tang, Kar Yan Tam
We present a new financial domain large language model, InvestLM, tuned on LLaMA-65B (Touvron et al., 2023), using a carefully curated instruction dataset related to financial inve…