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Tian Lan

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
same name
  • Tian Lan — 8 papers, h 24
  • Tian Lan — 6 papers
  • Tian Lan — 4 papers, h 19
  • Tian Lan — 3 papers, h 13
  • Tian Lan — 2 papers
  • Tian Lan — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedWhen to Talk: Chatbot Controls the Timing of Talking during Multi-turn Open-domain Dialogue Generation

2 citations · 4 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2022★ 1 cited

Momentum Decoding: Open-ended Text Generation As Graph Exploration

Tian Lan, Yixuan Su, Shuhang Liu +2

Open-ended text generation with autoregressive language models (LMs) is one of the core tasks in natural language processing. However, maximization-based decoding methods (e.g., gr…

cs.CL2022

Cross-Lingual Phrase Retrieval

Heqi Zheng, Xiao Zhang, Zewen Chi +5

Cross-lingual retrieval aims to retrieve relevant text across languages. Current methods typically achieve cross-lingual retrieval by learning language-agnostic text representation…

cs.CL2020★ 1 cited

Which Kind Is Better in Open-domain Multi-turn Dialog,Hierarchical or Non-hierarchical Models? An Empirical Study

Tian Lan, Xian-Ling Mao, Wei Wei +1

Currently, open-domain generative dialog systems have attracted considerable attention in academia and industry. Despite the success of single-turn dialog generation, multi-turn di…

cs.CL2019★ 2 cited

When to Talk: Chatbot Controls the Timing of Talking during Multi-turn Open-domain Dialogue Generation

Tian Lan, Xianling Mao, Heyan Huang +1

Despite the multi-turn open-domain dialogue systems have attracted more and more attention and made great progress, the existing dialogue systems are still very boring. Nearly all…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.