Papers by Yichen Gong
Recurrent Inference in Text Editing (2020.findings-emnlp)
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| Challenge: | Existing inference methods map the unedited text to the edited text or to the editing operations, but performance is degraded by the limited source text encoding and long, varying decoding steps. |
| Approach: | They propose a new inference method that iteratively performs editing actions . they introduce three types of editing tasks: AOR, AES, AEC . |
| Outcome: | The proposed method significantly narrows the problem space by iterating editing actions. |
FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering (2025.findings-acl)
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| Challenge: | Existing prompt-based debiasing methods exhibit instability due to sensitivity to prompt changes . fine-tuning-based techniques incur substantial computational overhead and catastrophic forgetting . |
| Approach: | They propose a debiasing framework that encodes fairness-related features into separable directions in the hidden activation space. |
| Outcome: | The proposed framework performs inference-time debiasing without requiring retraining or prompt design . it detects bias signatures in activations and then computes debiased steering vectors . the proposed framework is available to download in the u.s. |
Leveraging Unimodal Self-Supervised Learning for Multimodal Audio-Visual Speech Recognition (2022.acl-long)
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| Challenge: | Existing methods for audio-visual speech recognition use extra data to increase performance . a recent study shows that the use of unimodal self-supervised learning improves performance on multimodal tasks. |
| Approach: | They propose to use unimodal self-supervised learning to train AVSR models on unlabelled unilateral data. |
| Outcome: | The proposed model improves on lip reading sentences 2 by 30% even without an external language model. |