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20202023
most citedCausPref: Causal Preference Learning for Out-of-Distribution Recommendation

49 citations · 60 across the 10 of their papers we have counts for

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10 papers · 1 filter

cs.CL2023

On the (In)Effectiveness of Large Language Models for Chinese Text Correction

Yinghui Li, Haojing Huang, Shirong Ma +5

Recently, the development and progress of Large Language Models (LLMs) have amazed the entire Artificial Intelligence community. Benefiting from their emergent abilities, LLMs have…

cs.CL2023

Assisting Language Learners: Automated Trans-Lingual Definition Generation via Contrastive Prompt Learning

Hengyuan Zhang, Dawei Li, Yanran Li +3

The standard definition generation task requires to automatically produce mono-lingual definitions (e.g., English definitions for English words), but ignores that the generated def…

cs.CL2021

MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations

Xinyin Ma, Yong Jiang, Nguyen Bach +4

Entity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing. Recent progress in entit…

cs.CL20211 cited

Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings

Xinyu Wang, Zixia Jia, Yong Jiang +1

This paper describes the system used in submission from SHANGHAITECH team to the IWPT 2021 Shared Task. Our system is a graph-based parser with the technique of Automated Concatena…

cs.CL20217 cited

Towards Emotional Support Dialog Systems

Siyang Liu, Chujie Zheng, Orianna Demasi +5

Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats. Following reasonable proce…

cs.CL20211 cited

Diversifying Dialog Generation via Adaptive Label Smoothing

Yida Wang, Yinhe Zheng, Yong Jiang +1

Neural dialogue generation models trained with the one-hot target distribution suffer from the over-confidence issue, which leads to poor generation diversity as widely reported in…