Papers with autoencoder architecture

2 papers
How to Enhance Causal Discrimination of Utterances: A Case on Affective Reasoning (2023.emnlp-main)

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Challenge: Existing models excel at capturing semantic correlations within utterance embeddings but fail to determine specific causal relationships.
Approach: They propose to incorporate i.i.d. noise terms into conversation process to build a structural causal model . they propose to use unstructured conversation data to facilitate deep learning .
Outcome: The proposed approach can be implemented in unstructured conversation data and a synthetic dataset that includes i.i.d. noise.
SDR: Efficient Neural Re-ranking using Succinct Document Representation (2022.acl-long)

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Challenge: BERT based ranking models have been successful on various information retrieval tasks, but they are prone to storage and network fetching latency.
Approach: They propose a late-interaction architecture that allows pre-computation of intermediate document representations, thus reducing latency.
Outcome: The proposed model achieves 4x–11.6x higher compression rates on the MSMARCO passage re-reranking task compared to existing methods.

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