Caglar Gulcehre
Tenure Track Assistant Professor
Leads the CLAIRE lab, working on reinforcement learning, foundation models, sequence-model architectures and alignment of language models.
Caglar Gulcehre's lab at EPFL works on reinforcement learning, generative & foundation models and large language models. 13 papers since 2023, 9 at top venues, mostly NeurIPS and ICLR. 8 PhD students. Applications close .
At a glance
- papers, 2023–2026
- 3/ year
- at T1 venues
- 69%
- PhD students
- 8
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 2 papers2026 · T1 0 · collecting
- 6 papers2025 · T1 4
- 4 papers2024 · T1 4
- 1 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, ICLR, EMNLP
Research focuspaper titles that use each topic's words
- Large language models6 papers
- Reinforcement learning3 papers
- Generative & foundation models3 papers
- alignment1 paper
- communication sciences0 papers
Paper list
From the lab homepage.
20262 papers
- Games: Research and PracticeContext-Aware Toxicity Detection in Game Chat: Domain-Adaptive Pretraining with Match Metadata under Limited Labels (opens in a new tab)
- IEEE Signal Processing MagazineSequence Modeling Architectures: Foundations [Special Issue on the Mathematics of Deep Learning] (opens in a new tab)
20256 papers
- Second Conference on Language Modeling COLMAlgorithm Discovery With LLMs: Evolutionary Search Meets Reinforcement Learning
- ICLR (T1)Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
- NeurIPS (T1)One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models (opens in a new tab)
- NeurIPS (T1)Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions (opens in a new tab)
- NeurIPS (T1)RAT: Bridging RNN Efficiency and Attention Accuracy via Chunk-based Sequence Modeling (opens in a new tab)
- ICAIFRegret-Optimized Portfolio Enhancement through Deep Reinforcement Learning and Future Looking Rewards (opens in a new tab)
20244 papers
- NeurIPS (T1)Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers
- NeurIPS (T1)No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
- EMNLP (T1)Self-Recognition in Language Models
- ICLR (T1)Simple Hierarchical Planning with Diffusion
Where alumni went
Alumni are not listed on the lab homepage.
Apply to EPFLFall 2027
EDIC Computer and Communication Sciences PhD
- Round
- Round 1
- Opens
- —
- GRE
- optional
- English
- TOEFL 100 / IELTS 7.0
- Fee
- none
Confirmed on the program page.
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Data
Some numbers could not be verified:
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.
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