activity
20132023
most citedDailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

667 citations · 740 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2023★ 1 cited

Social4Rec: Distilling User Preference from Social Graph for Video Recommendation in Tencent

Xuanji Xiao, Huaqiang Dai, Qian Dong +3

Despite recommender systems play a key role in network content platforms, mining the user's interests is still a significant challenge. Existing works predict the user interest by…

cs.IR2022

Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking

Qian Dong, Yiding Liu, Suqi Cheng +4

Passage re-ranking is to obtain a permutation over the candidate passage set from retrieval stage. Re-rankers have been boomed by Pre-trained Language Models (PLMs) due to their ov…

cs.CL2018★ 31 cited

Improving Variational Encoder-Decoders in Dialogue Generation

Xiaoyu Shen, Hui Su, Shuzi Niu +1

Variational encoder-decoders (VEDs) have shown promising results in dialogue generation. However, the latent variable distributions are usually approximated by a much simpler model…

cs.CL2017★ 667 cited

DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset

Yanran Li, Hui Su, Xiaoyu Shen +3

We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset…

cs.CL2017★ 29 cited

A Conditional Variational Framework for Dialog Generation

Xiaoyu Shen, Hui Su, Yanran Li +5

Deep latent variable models have been shown to facilitate the response generation for open-domain dialog systems. However, these latent variables are highly randomized, leading to…

cs.LG2013★ 12 cited

Stochastic Rank Aggregation

Shuzi Niu, Yanyan Lan, Jiafeng Guo +1

This paper addresses the problem of rank aggregation, which aims to find a consensus ranking among multiple ranking inputs. Traditional rank aggregation methods are deterministic,…