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Found 12 papers, 7 papers with code
TSDAE: Using Transformer-based Sequential Denoising Auto-Encoderfor Unsupervised Sentence Embedding Learning
Learning sentence embeddings often requires a large amount of labeled data.
DAPR: A Benchmark on Document-Aware Passage Retrieval
To fill this gap, we propose and name this task Document-Aware Passage Retrieval (DAPR) and build a benchmark including multiple datasets from various domains, covering both DAPR and whole-document retrieval.
UKP-SQuARE v3: A Platform for Multi-Agent QA Research
To ease research in multi-agent models, we extend UKP-SQuARE, an online platform for QA research, to support three families of multi-agent systems: i) agent selection, ii) early-fusion of agents, and iii) late-fusion of agents.
Semantic Similarity Models for Depression Severity Estimation
Depressive disorders constitute a severe public health issue worldwide.
UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA
In this paper, we introduce SQuARE v2, the new version of SQuARE, to provide an explainability infrastructure for comparing models based on methods such as saliency maps and graph-based explanations.
RT-KGD: Relation Transition Aware Knowledge-Grounded Dialogue Generation
Nevertheless, the correlations between knowledge implied in the multi-turn context and the transition regularities between relations in KGs are under-explored.
UKP-SQUARE: An Online Platform for Question Answering Research
Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e. g., extractive, abstractive), require different model architectures (e. g., generative, discriminative), and setups (e. g., with or without retrieval).
GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval
This limits the usage of dense retrieval approaches to only a few domains with large training datasets.
Ranked #9 on
Zero-shot Text Search
on BEIR
TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning
Learning sentence embeddings often requires a large amount of labeled data.
Ranked #1 on
Paraphrase Identification
on TURL
An Emotion-controlled Dialog Response Generation Model with Dynamic Vocabulary
In response generation task, proper sentimental expressions can obviously improve the human-like level of the responses.
A New Modal Autoencoder for Functionally Independent Feature Extraction
Autoencoders have been widely used for dimensional reduction and feature extraction.
Understanding Memory Modules on Learning Simple Algorithms
Recent work has shown that memory modules are crucial for the generalization ability of neural networks on learning simple algorithms.
