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Found 14 papers, 11 papers with code
Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization
In this article, we address this challenge by exploring a series of domain adaptation techniques.
MealRec$^+$: A Meal Recommendation Dataset with Meal-Course Affiliation for Personalization and Healthiness
Due to constraints related to user health privacy and meal scenario characteristics, the collection of data that includes both meal-course affiliation and two levels of interactions is impeded.
A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets
The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently.
Ranked #8 on
Natural Language Inference
on ANLI test
Prompt Learning to Mitigate Catastrophic Forgetting in Cross-lingual Transfer for Open-domain Dialogue Generation
Dialogue systems for non-English languages have long been under-explored.
Hypergraph Contrastive Collaborative Filtering
Additionally, our HCCF model effectively integrates the hypergraph structure encoding with self-supervised learning to reinforce the representation quality of recommender systems, based on the hypergraph-enhanced self-discrimination.
Domain Adaptation with Pre-trained Transformers for Query Focused Abstractive Text Summarization
In this paper, we address this challenge by exploring a series of domain adaptation techniques.
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation
The learning process of intra- and inter-session transition dynamics are integrated, to preserve the underlying low- and high-level item relationships in a common latent space.
A Contextual Alignment Enhanced Cross Graph Attention Network for Cross-lingual Entity Alignment
In this paper, we propose a novel Contextual Alignment Enhanced Cross Graph Attention Network (CAECGAT) for the task of cross-lingual entity alignment, which is able to jointly learn the embeddings in different KGs by propagating cross-KG information through pre-aligned seed alignments.
Utilizing Bidirectional Encoder Representations from Transformers for Answer Selection
We find that fine-tuning the BERT model for the answer selection task is very effective and observe a maximum improvement of 13. 1% in the QA datasets and 18. 7% in the CQA datasets compared to the previous state-of-the-art.
WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive Summarization
In the Query Focused Multi-Document Summarization (QF-MDS) task, a set of documents and a query are given where the goal is to generate a summary from these documents based on the given query.
Neural Interactive Collaborative Filtering
Therefore, the proposed exploration policy, to balance between learning the user profile and making accurate recommendations, can be directly optimized by maximizing users' long-term satisfaction with reinforcement learning.
ReInceptionE: Relation-Aware Inception Network with Joint Local-Global Structural Information for Knowledge Graph Embedding
In this paper, we take the benefits of ConvE and KBGAT together and propose a Relation-aware Inception network with joint local-global structural information for knowledge graph Embedding (ReInceptionE).
Contextualized Embeddings based Transformer Encoder for Sentence Similarity Modeling in Answer Selection Task
In this paper, we utilize contextualized word embeddings with the transformer encoder for sentence similarity modeling in the answer selection task.
