Mingda Chen
副教授
Works on text and multimodal large language models, having contributed to ALBERT, Chameleon and LLaMA.
Mingda Chen's lab at SJTU works on large language models, multimodal & grounded language and vision-language & multimodal. 8 papers since 2023, 5 at top venues, mostly ACL and EACL. Applications close .
At a glance
- papers, 2023–2026
- 2/ year
- at T1 venues
- 63%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 3 papers2025 · T1 2
- 1 papers2024 · T1 0
- 4 papers2023 · T1 3
T1 venuesOtherVenues: ACL, EACL, Findings of EMNLP, ICLR, MICRO
Research focuspaper titles that use each topic's words
- Multimodal & grounded language1 paper
- Vision-language & multimodal1 paper
- text1 paper
- Large language models0 papers
- multimodal large0 papers
Paper list
From the lab homepage.
20253 papers
- Findings of EMNLP😈ImpRAG: Retrieval-Augmented Generation with Implicit Queries
- MICRO (T1)Characterizing and Efficiently Accelerating Multimodal Generation Model Inference
- ACL (T1)Improving Factuality with Explicit Working Memory
20241 paper
- EACLFew-Shot Data Synthesis for Open-Domain Multi-Hop Question Answering
20234 papers
- ACL (T1)BLASER: A Text-Free Speech-to-Speech Translation Evaluation Metric
- Proceedings of IWSLTFindings of the IWSLT 2023 Evaluation Campaign
- ICLR (T1)RA-DIT: Retrieval-Augmented Dual Instruction Tuning
- ACL (T1)xSIM: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages
Where alumni went
Alumni are not listed on the lab homepage.
Apply to SJTUFall 2027
Computer Science PhD (international applicants)
- Round
- Self-funded
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Your notes
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Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Not collected
- Alumni
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