Papers by Jinning Li
Measuring the Effect of Influential Messages on Varying Personas (2023.acl-short)
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| Challenge: | a new task estimates the response a persona might have upon seeing a news message . a first benchmark dataset is used to evaluate the performance of the proposed task . |
| Approach: | They propose a task to estimate the response a persona might have upon seeing a news message. |
| Outcome: | The proposed task estimates the response a persona might have upon seeing a news message. |
Noisy Positive-Unlabeled Learning with Self-Training for Speculative Knowledge Graph Reasoning (2023.findings-acl)
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Ruijie Wang, Baoyu Li, Yichen Lu, Dachun Sun, Jinning Li, Yuchen Yan, Shengzhong Liu, Hanghang Tong, Tarek Abdelzaher
| Challenge: | State-of-the-art methods fail in speculative reasoning task on knowledge graphs . state-of the-art approaches assume correctness of fact is determined by its presence in KG . |
| Approach: | They propose a speculative reasoning task on real-world knowledge graphs . they propose nPUGraph that estimates correctness of both collected and uncollected facts . |
| Outcome: | The proposed framework improves the robustness of a label posterior-aware graph encoder against false positive links and identifies missing facts to provide high-quality grounds of reasoning. |
Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecasting (2023.emnlp-main)
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| Challenge: | Existing approaches to forecast news media responses have limited exploration of how to best process and utilize these important features. |
| Approach: | They propose a framework that leverages a large language model to induce a belief-centered graph on top of an existent social network, along with graph-based propagation to capture social dynamics. |
| Outcome: | The proposed framework surpasses state-of-the-art in experimental evaluations for both zero-shot and supervised settings, demonstrating its effectiveness in response forecasting. |