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Jing Liu

19 papers hereh-index 6141 citations22 works total

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

author position
  • sole author2
  • first author3
  • middle author12

Across the 17 of 19 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.CV3
  • cs.LG3
  • cs.SE3
  • cs.AI2
  • cs.CY2
same name
  • Jing Liu — 28 papers, h 6
  • Jing Liu — 23 papers, h 15
  • Jing Liu — 17 papers, h 11
  • Jing Liu — 16 papers, h 8
  • Jing Liu — 12 papers
  • Jing Liu — 12 papers, h 5

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 citedLLM4Fuzz: Guided Fuzzing of Smart Contracts with Large Language Models

8 citations · 13 across the 19 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026★ 2 cited

ERNIE 5.0 Technical Report

Haifeng Wang, Hua Wu, Tian Wu +432

In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…

cs.CL2025

A Survey on Parallel Reasoning

Ziqi Wang, Boye Niu, Zipeng Gao +10

With the increasing capabilities of Large Language Models (LLMs), parallel reasoning has emerged as a new inference paradigm that enhances reasoning robustness by concurrently expl…

cs.CL2025

Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM

Ryan Solgi, Parsa Madinei, Jiayi Tian +4

Large language models (LLM) and vision-language models (VLM) have achieved state-of-the-art performance, but they impose significant memory and computing challenges in deployment.…

cs.CL2025

Knowledge-Level Consistency Reinforcement Learning: Dual-Fact Alignment for Long-Form Factuality

Junliang Li, Yucheng Wang, Yan Chen +5

Hallucination in large language models (LLMs) during long-form generation remains difficult to address under existing reinforcement learning from human feedback (RLHF) frameworks,…

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