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Jiarui Wang

33 papers hereh-index 15674 citations67 works total

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

author position
  • first author6
  • middle author25

Across the 31 of 33 papers where every author was matched, so the position is known.

fields
  • cs.CV25
  • cs.CL4
  • cs.DC1
  • cs.IR1
  • cs.LG1
  • eess.IV1
same name
  • Jiarui Wang — 3 papers, h 5
  • Jiarui Wang — 3 papers, h 19
  • Jiarui Wang — 2 papers, h 2
  • Jiarui Wang — 1 paper, h 6
  • Jiarui Wang — 1 paper, h 1
  • Jiarui Wang — 1 paper, h 1

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

works on
language models 1long-term memory 1parameter efficiency 1retrieval 1scaling 1

From the 1 of 33 linked papers with an AI index.

activity
20242026
collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

Memory Decoder at Scale: A Pretrained, Parametric Long-Term Memory

Rubin Wei, Jiaqi Cao, Jiarui Wang +4

The paper presents Memory Decoder at Scale, a pretrained parametric long‑term memory module for decoder‑only language models that is scaled up to 6.9 B parameters and shown to impr…

cs.CL2026★ 1 cited

MLP Memory: A Retriever-Pretrained Memory for Large Language Models

Rubin Wei, Jiaqi Cao, Jiarui Wang +4

Modern approaches to enhancing Large Language Models' factual accuracy and knowledge utilization face a fundamental trade-off: non-parametric retrieval-augmented generation (RAG) p…

cs.CL2026

d2Cache: Accelerating Diffusion-Based LLMs via Dual Adaptive Caching

Yuchu Jiang, Yue Cai, Xiangzhong Luo +4

Diffusion-based large language models (dLLMs), despite their promising performance, still suffer from inferior inference efficiency. This is because dLLMs rely on bidirectional att…

cs.CL2025

Memory Decoder: A Pretrained, Plug-and-Play Memory for Large Language Models

Jiaqi Cao, Jiarui Wang, Rubin Wei +4

Large Language Models (LLMs) have shown strong abilities in general language tasks, yet adapting them to specific domains remains a challenge. Current method like Domain Adaptive P…

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