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researcher

Caiming Xiong

51 papers hereh-index 3918.5k citations99 works total

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

author position
  • middle author28
  • last author21

Across the 49 of 51 papers where every author was matched, so the position is known.

fields
  • cs.CL34
  • cs.CV5
  • cs.IR5
  • cs.AI4
  • cs.LG3
same name
  • Caiming Xiong — 107 papers, h 73
  • Caiming Xiong — 75 papers, h 27
  • Caiming Xiong — 27 papers, h 15
  • Caiming Xiong — 24 papers, h 16
  • Caiming Xiong — 22 papers, h 11
  • Caiming Xiong — 16 papers

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
20202024
most citedBLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

871 citations · 2.3k across the 35 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2023★ 9 cited

BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

Zhiwei Liu, Weiran Yao, Jianguo Zhang +12

The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs). An LAA is able to generate actions with its core…

cs.AI2023

REX: Rapid Exploration and eXploitation for AI Agents

Rithesh Murthy, Shelby Heinecke, Juan Carlos Niebles +12

In this paper, we propose an enhanced approach for Rapid Exploration and eXploitation for AI Agents called REX. Existing AutoGPT-style techniques have inherent limitations, such as…

cs.AI2022★ 404 cited

Intent Contrastive Learning for Sequential Recommendation

Yongjun Chen, Zhiwei Liu, Jia Li +2

Users' interactions with items are driven by various intents (e.g., preparing for holiday gifts, shopping for fishing equipment, etc.).However, users' underlying intents are often…

cs.AI2021★ 9 cited

Modeling Dynamic Attributes for Next Basket Recommendation

Yongjun Chen, Jia Li, Chenghao Liu +4

Traditional approaches to next item and next basket recommendation typically extract users' interests based on their past interactions and associated static contextual information…

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