Feng Shi

Few-shot Multimodal Sentiment Analysis based on Multimodal Probabilistic Fusion Prompts

2022 · arXiv (Cornell University)

Multimodal sentiment analysis has gained significant attention due to the proliferation of multimodal content on social media. However, existing studies in this area rely heavily on large-scale supervised data, which is time-consuming and labor-intensive to …

Contrastive Learning with Generated Representations for Inductive Knowledge Graph Embedding

2023

With the evolution of Knowledge Graphs (KGs), new entities emerge which are not seen before. Representation learning of KGs in such an inductive setting aims to capture and transfer the structural patterns from existing entities …

KARL: Knowledge-Aware Retrieval and Representations aid Retention and Learning in Students

2024 · arXiv (Cornell University)

Flashcard schedulers rely on 1) student models to predict the flashcards a student knows; and 2) teaching policies to pick which cards to show next via these predictions. Prior student models, however, just use study …

Sharp Results for Hypothesis Testing with Risk-Sensitive Agents

2024 · arXiv (Cornell University)

Statistical protocols are often used for decision-making involving multiple parties, each with their own incentives, private information, and ability to influence the distributional properties of the data. We study a game-theoretic version of hypothesis testing …

Active Example Selection for In-Context Learning

2022

With a handful of demonstration examples, large-scale language models demonstrate strong capability to perform various tasks by in-context learning from these examples, without any fine-tuning. We demonstrate that in-context learning performance can be highly unstable …