Albert Gu
Assistant Professor
Develops deep learning architectures and representation learning methods, including state space sequence models.
Albert Gu's lab at CMU works on generative & foundation models and accelerators, chips & architecture. 19 papers since 2023, 15 at top venues, mostly ICLR and ICML. 6 PhD students and 1 master's student. Applications close .
At a glance
- papers, 2023–2026
- 5/ year
- at T1 venues
- 79%
- PhD students
- 6
- MS students
- 1
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 4 papers2026 · T1 3 · collecting
- 5 papers2025 · T1 3
- 5 papers2024 · T1 5
- 5 papers2023 · T1 4
T1 venuesOtherVenues: ICLR, ICML, NeurIPS, Findings of EMNLP, ICASSP
Research focuspaper titles that use each topic's words
- Generative & foundation models11 papers
- state7 papers
- space7 papers
- sequence5 papers
- Accelerators, chips & architecture0 papers
Paper list
From DBLP.
20264 papers
- ICLR (T1)Dynamic Chunking for End-to-End Hierarchical Sequence Modeling (opens in a new tab)
- ICLR (T1)Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models (opens in a new tab)
- ICLR (T1)Mamba-3: Improved Sequence Modeling using State Space Principles (opens in a new tab)
- IEEE Signal Process. Mag.Sequence Modeling Architectures: Foundations [Special Issue on the Mathematics of Deep Learning] (opens in a new tab)
20255 papers
- Trans. Mach. Learn. Res.Chimera: State Space Models Beyond Sequences (opens in a new tab)
- ICLR (T1)On the Benefits of Memory for Modeling Time-Dependent PDEs (opens in a new tab)
- NAACL WorkshopTowards Codec-LM Co-design for Neural Codec Language Models (opens in a new tab)
- ICML (T1)Understanding and Improving Length Generalization in Recurrent Models (opens in a new tab)
- ICML (T1)Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism (opens in a new tab)
20245 papers
- ICASSP (T1)Augmenting Conformers With Structured State-Space Sequence Models For Online Speech Recognition (opens in a new tab)
- ICML (T1)Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling (opens in a new tab)
- NeurIPS (T1)Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers (opens in a new tab)
- ICML (T1)Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality (opens in a new tab)
- NeurIPS (T1)Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models (opens in a new tab)
20235 papers
- ICLR (T1)How to Train your HIPPO: State Space Models with Generalized Orthogonal Basis Projections (opens in a new tab)
- ICLR (T1)Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN (opens in a new tab)
- Findings of EMNLPPretraining Without Attention (opens in a new tab)
- ICML (T1)Resurrecting Recurrent Neural Networks for Long Sequences (opens in a new tab)
- NeurIPS (T1)Structured State Space Models for In-Context Reinforcement Learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to CMUFall 2027
CMU SCS Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL / IELTS / Duolingo (F-1/J-1 non-native speakers)
- Fee
- USD 100 (USD 80 by early deadline)
Confirmed on the program page.
Similar labsnearest by research summary
- CNPeking
Yinjun Wu
- Data management & big data
- USMIT
Martin Wainwright
- Learning theory & optimization
- CNZhejiang
Lei Cheng
- Learning theory & optimization
- GBImperial
Francesco Belardinelli
- Reasoning & neuro-symbolic AI
- USCMU
Kun Zhang
- Probabilistic & causal inference
- USStanford
James Zou
- Trustworthy & safe ML
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- DBLP
- Members
- Lab homepage
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.
CMUcloses