Eldan Cohen
Assistant Professor
Studies combinatorial search and optimization combined with machine learning, including decoding in sequence models.
Eldan Cohen's lab at Toronto works on learning theory & optimization. 29 papers since 2023, 4 at top venues, mostly NeurIPS and ACL. 11 PhD students and 1 master's student. 7 alumni. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 14%
- PhD students
- 11
- MS students
- 1
- alumni listed
- 7
Papers by yearfrom the lab homepage, 2023–2026
- 8 papers2026 · T1 2 · collecting
- 8 papers2025 · T1 1
- 8 papers2024 · T1 0
- 5 papers2023 · T1 1
T1 venuesOtherVenues: NeurIPS, ACL, IJCAI, Journal of Artificial Intelligence Research, SLT
Research focuspaper titles that use each topic's words
- Learning theory & optimization9 papers
- sequence1 paper
- combinatorial0 papers
- decoding0 papers
- industrial engineering0 papers
Paper list
From the lab homepage.
20268 papers
- LIONCP-SynC: Multi-Agent Zero-Shot Constraint Modeling in MiniZinc with Synthesized Checkers
- ISSTADo Coverage and Mutation Scores of LLM-Generated Test Suites Correlate With Their Effectiveness? (Replicability Study)
- ISSTAEvaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests
- ACL (T1)Lightweight and Faithful Visual Condition Checking in Behavior Trees via Expert-Regularized Reinforcement Learning
- NeurIPS (T1)Literati: Towards Anytime Optimal Shape Generalized Trees via AO*
- JMIR medical informaticsMachine Learning to Prioritize High-Severity Patient Safety Events for Institutional Investigation: Algorithm Development and Validation Study
- SoCSMake Use of Your Search Effort: Data Augmentation for Learning Effective Planning Heuristics from Optimal Plans
- SLTPrompt-Aware Gated Cross-Attention for Multi-Encoder Large Audio Language Models
20258 papers
- LION-25Do LLMs Understand Constraint Programming? Zero-Shot Constraint Programming Model Generation Using LLMs
- JMIR Medical InformaticsEfficient Detection of Stigmatizing Language in Electronic Health Records via In-Context Learning: A Comparative Analysis and Validation Study
- NeurIPS (T1)Empowering Decision Trees via Shape Function Branching
- ErgonomicsExamining the development, effectiveness, and limitations of computer-aided diagnosis systems for retained surgical items detection: a systematic review
- Frontiers in MedicineLeveraging LLM to identify missed information in patient-physician communication: improving healthcare service quality
- Journal of Artificial Intelligence ResearchOptimal Decision Trees for Interpretable and Constrained Clustering
- CASE-25ROCKET-LRP: Explainable Time Series Classification with Application to Anomaly Prediction in Manufacturing
- Journal of Systems and SoftwareVariational Prefix Tuning for Diverse and Accurate Code Summarization Using Pre-trained Language Models
20248 papers
- JMIR Human FactorsAutomated Classification of Patient Safety Event Reports: A Machine Learning Approach with Human-AI Collaboration
- SoCS-24Bi-Criteria Diverse Plan Selection via Beam Search Approximation
- Proceedings of the Human Factors and Ergonomics Society Annual MeetingEvaluating Active Learning Strategies for Automated Classification of Patient Safety Event Reports in Hospitals
- NAACL-24Gaussian Process Optimization for Adaptable Multi-Objective Text Generation using Linearly-Weighted Language Models
- JMIR Formative ResearchIntersection of Performance, Interpretability, and Fairness in Neural Prototype Tree for Chest X-Ray Pathology Detection: Algorithm Development and Validation Study
- SoCS-24Neural Sequence Generation with Constraints via Beam Search with Cuts: A Case Study on VRP
- ECAI-24NeurCAM: Interpretable Neural Clustering via Additive Models
- Engineering Applications of Artificial IntelligenceTransformer models for mining intents and predicting activities from emails in knowledge-intensive processes
20235 papers
- Proceedings of the Human Factors and Ergonomics Society Annual MeetingImproving Patient Safety Event Report Classification with Machine Learning and Contextual Text Representation
- CPAIORInterpretable Clustering via Soft Clustering Trees
- IJCAI (T1)Optimal Decision Trees For Interpretable Clustering with Constraints
- CPSAT-Based Learning of Compact Binary Decision Diagrams for Classification
- ConstraintsSAT-based optimal classification trees for non-binary data
Where alumni went7 listed
Apply to TorontoFall 2027
Computer Science MSc/PhD
- Round
- Single round (Dec 1)
- Opens
- —
- GRE
- optional
- English
- TOEFL/IELTS if applicable
- Fee
- CAD 135
Confirmed on the program page.
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