Papers with counterfactual generation
Episodic Memory Retrieval from LLMs: A Neuromorphic Mechanism to Generate Commonsense Counterfactuals for Relation Extraction (2024.findings-acl)
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| Challenge: | Large language models (LLMs) have achieved satisfactory performance in counterfactual generation, however, there are misalignments between LLMs and humans which hinder LLM from handling complex tasks like relation extraction. |
| Approach: | They propose to mimic the episodic memory retrieval mechanism of human hippocampus to align LLMs’ generation process with that of humans. |
| Outcome: | The proposed framework improves over existing methods in terms of quality of counterfactuals. |
CPL: Counterfactual Prompt Learning for Vision and Language Models (2022.emnlp-main)
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Xuehai He, Diji Yang, Weixi Feng, Tsu-Jui Fu, Arjun Akula, Varun Jampani, Pradyumna Narayana, Sugato Basu, William Yang Wang, Xin Wang
| Challenge: | Existing prompt tuning methods tend to learn spurious or entangled representations, leading to poor generalization to unseen concepts. |
| Approach: | They propose a prompt tuning technique that tunes the learnable prompt for pre-trained vision and language models. |
| Outcome: | The proposed method improves few-shot performance on vision and language tasks over existing prompt tuning methods. |
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns (2023.eacl-main)
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| Challenge: | a number of studies have focused on gender bias in language models, but these methods fail to detect it. |
| Approach: | They propose to use gender bias in coreference resolution to evaluate gender bias . they propose to construct an annotated quadruple-level dataset with 4008 instances . |
| Outcome: | The proposed method is able to detect gender bias in a quadruple dataset . previous methods failed to detect bias or cancel it, the authors argue . |