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Sicong Leng

21 papers hereh-index 142.5k citations32 works total

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

author position
  • first author3
  • middle author13
  • last author2

Across the 18 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.CL4
  • cs.RO4
  • cs.AI1
  • cs.LG1
same name
  • Sicong Leng — 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
20212026
most citedSpeaker-Oriented Latent Structures for Dialogue-Based Relation Extraction

7 citations · 12 across the 13 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

Advancing Expert Specialization for Better MoE

Hongcan Guo, Haolang Lu, Guoshun Nan +8

Mixture-of-Experts (MoE) models enable efficient scaling of large language models (LLMs) by activating only a subset of experts per input. However, we observe that the commonly use…

cs.CL2025

Refining Positive and Toxic Samples for Dual Safety Self-Alignment of LLMs with Minimal Human Interventions

Jingxin Xu, Guoshun Nan, Sheng Guan +7

Recent AI agents, such as ChatGPT and LLaMA, primarily rely on instruction tuning and reinforcement learning to calibrate the output of large language models (LLMs) with human inte…

cs.CL2023

Tell2Design: A Dataset for Language-Guided Floor Plan Generation

Sicong Leng, Yang Zhou, Mohammed Haroon Dupty +3

We consider the task of generating designs directly from natural language descriptions, and consider floor plan generation as the initial research area. Language conditional genera…

cs.CL2021★ 7 cited

Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction

Guoshun Nan, Guoqing Luo, Sicong Leng +2

Dialogue-based relation extraction (DiaRE) aims to detect the structural information from unstructured utterances in dialogues. Existing relation extraction models may be unsatisfa…

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