◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Liqiang Nie

20 papers hereh-index 9270 citations21 works total

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

author position
  • middle author12
  • last author8

Across the 20 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.CL4
  • cs.AI3
  • cs.IR2
  • cs.MM2
  • cs.LG1
same name
  • Liqiang Nie — 86 papers, h 79
  • Liqiang Nie — 44 papers, h 18
  • Liqiang Nie — 32 papers, h 7
  • Liqiang Nie — 23 papers, h 12
  • Liqiang Nie — 22 papers, h 11
  • Liqiang Nie — 13 papers, h 16

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
20242026
most citedA Survey of Generative Search and Recommendation in the Era of Large Language Models

2 citations · 3 across the 18 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

Parallel Test-Time Scaling for Latent Reasoning Models

Runyang You, Yongqi Li, Meng Liu +3

Parallel test-time scaling (TTS) is a pivotal approach for enhancing large language models (LLMs), typically by sampling multiple token-based chains-of-thought in parallel and aggr…

cs.CL2025

Towards Harmless Multimodal Assistants with Blind Preference Optimization

Yongqi Li, Lu Yang, Jian Wang +3

Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in multimodal understanding, reasoning, and interaction. Given the extensive applications of MLLM…

cs.CL2024

Distillation Enhanced Generative Retrieval

Yongqi Li, Zhen Zhang, Wenjie Wang +3

Generative retrieval is a promising new paradigm in text retrieval that generates identifier strings of relevant passages as the retrieval target. This paradigm leverages powerful…

cs.CL2024

GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding

Cunxiao Du, Jing Jiang, Xu Yuanchen +8

Speculative decoding is a relatively new decoding framework that leverages small and efficient draft models to reduce the latency of LLMs. In this study, we introduce GliDe and CaP…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.