Christopher Manning
Professor
Studies natural language processing with deep learning, including language understanding and parsing.
Christopher Manning's lab at Stanford works on multilingual, translation & linguistics. 57 papers since 2023, 37 at top venues, mostly ICLR and EMNLP. Applications close .
At a glance
- papers, 2023–2026
- 15/ year
- at T1 venues
- 65%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage and DBLP, 2023–2026
- 8 papers2026 · T1 5 · collecting
- 19 papers2025 · T1 11
- 12 papers2024 · T1 10
- 18 papers2023 · T1 11
T1 venuesOtherVenues: ICLR, EMNLP, NeurIPS, Findings of ACL, ICML
Research focuspaper titles that use each topic's words
- language26 papers
- Multilingual, translation & linguistics2 papers
- parsing1 paper
- language understanding0 papers
- studies natural0 papers
Paper list
From the lab homepage and DBLP.
20268 papers
- JOURNAL OF LEGAL ANALYSISAI for scaling legal reform: mapping and redacting racial covenants in Santa Clara County (opens in a new tab)
- PNAS (T1)At the boundary: Law and AI. (opens in a new tab)
- ICLR (T1)DistillKac: Few-Step Image Generation via Damped Wave Equations (opens in a new tab)
- EACLHumans and transformer LMs: Abstraction drives language learning (opens in a new tab)
- Commun. ACMNatural Language Processing: How NSF Supports Visionary New Approaches to NLP (opens in a new tab)
- PNAS (T1)There is no free benchmark: An institutional view of legal AI benchmarking. (opens in a new tab)
- ICLR (T1)Tversky Neural Networks: Psychologically Plausible Deep Learning with Differentiable Tversky Similarity (opens in a new tab)
- ICLR (T1)WebDS: An End-to-End Benchmark for Web-based Data Science (opens in a new tab)
202519 papers
- NeurIPS (T1)A Multimodal Benchmark for Framing of Oil & Gas Advertising and Potential Greenwashing Detection (opens in a new tab)
- CSLAWA Reasoning-Focused Legal Retrieval Benchmark (opens in a new tab)
- ICLR (T1)AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark (opens in a new tab)
- ICML (T1)AXBENCH: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders (opens in a new tab)
- NeurIPS (T1)Do Language Models Use Their Depth Efficiently? (opens in a new tab)
- Findings of ACLDrop Dropout on Single Epoch Language Model Pretraining (opens in a new tab)
- ICLR (T1)h4rm3l: A Language for Composable Jailbreak Attack Synthesis (opens in a new tab)
- JOURNAL OF EMPIRICAL LEGAL STUDIESHallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools (opens in a new tab)
- IWPTHigh-Accuracy Transition-Based Constituency Parsing (opens in a new tab)
- NeurIPS (T1)Improved Representation Steering for Language Models (opens in a new tab)
- Findings of NAACLLawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain (opens in a new tab)
- EMNLP (T1)Mechanisms vs. Outcomes: Probing for Syntax Fails to Explain Performance on Targeted Syntactic Evaluations (opens in a new tab)
202412 papers
- ICLR (T1)An Emulator for Fine-tuning Large Language Models using Small Language Models (opens in a new tab)
- ICML (T1)BAGEL: Bootstrapping Agents by Guiding Exploration with Language (opens in a new tab)
- ICLR (T1)Fine-Tuning Language Models for Factuality (opens in a new tab)
- L@SHandwritten Code Recognition for Pen-and-Paper CS Education (opens in a new tab)
- ICLR (T1)Language Model Detectors Are Easily Optimized Against (opens in a new tab)
- NeurIPS (T1)MoEUT: Mixture-of-Experts Universal Transformers (opens in a new tab)
- Findings of ACLPredicting Narratives of Climate Obstruction in Social Media Advertising (opens in a new tab)
- NAACL (T1)pyvene: A Library for Understanding and Improving PyTorch Models via Interventions (opens in a new tab)
- ICLR (T1)RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval (opens in a new tab)
- NeurIPS (T1)ReFT: Representation Finetuning for Language Models (opens in a new tab)
- IJCAI (T1)ReportParse: A Unified NLP Tool for Extracting Document Structure and Semantics of Corporate Sustainability Reporting (opens in a new tab)
- EMNLP (T1)Statistical Uncertainty in Word Embeddings: GloVe-V (opens in a new tab)
202318 papers
- NeurIPS (T1)An NLP Benchmark Dataset for Assessing Corporate Climate Policy Engagement (opens in a new tab)
- ACL (T1)Backpack Language Models (opens in a new tab)
- Trans. Mach. Learn. Res.Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (opens in a new tab)
- ICLR (T1)Characterizing intrinsic compositionality in transformers with Tree Projections (opens in a new tab)
- ICML (T1)DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature (opens in a new tab)
- NeurIPS (T1)Direct Preference Optimization: Your Language Model is Secretly a Reward Model (opens in a new tab)
- Findings of EMNLPDo "English" Named Entity Recognizers Work Well on Global Englishes? (opens in a new tab)
- ACL (T1)Grokking of Hierarchical Structure in Vanilla Transformers (opens in a new tab)
- Trans. Mach. Learn. Res.Holistic Evaluation of Language Models (opens in a new tab)
- EMNLP (T1)Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback (opens in a new tab)
- WMTMachine Translation for Nko: Tools, Corpora, and Baseline Results (opens in a new tab)
- EMNLP (T1)Meta-Learning Online Adaptation of Language Models (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to StanfordFall 2027
Stanford Computer Science PhD
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- Single round
- Opens
- GRE
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- English
- TOEFL/IELTS
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Confirmed on the program page.
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Data
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- The alumni list could not be found on the lab site.
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- Members
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- Alumni
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