--- title: "Michel Galley — papers and cards" description: "Michel Galley: 2 paper cards in the Research library (2004–2006), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/michel-galley/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/michel-galley/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Michel Galley # Michel Galley 2 paper cards in the Research library · 2004–2006 Michel Galley wrote 2 of the papers Mova reads, in 2004–2006, most of them on [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/); often with [Daniel Marcu](https://md.research.elamur.ai/free/en/authors/daniel-marcu/), [Kevin Knight](https://md.research.elamur.ai/free/en/authors/kevin-knight/), Ignacio Thayer. [OpenAlex](https://openalex.org/A5107838508) · [**h-index 49**](https://openalex.org/authors/A5107838508) · [14089 citations](https://openalex.org/authors/A5107838508) · [135 works](https://openalex.org/works?filter=author.id:A5107838508) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Michel+Galley) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Michel+Galley) · [dblp](https://dblp.org/search?q=Michel+Galley) · [ACL Anthology](https://aclanthology.org/search/?q=Michel+Galley) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Michel+Galley) Topics: [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) 2 ## Papers 1. **[Scalable Inference and Training of Context-Rich Syntactic Translation Models](https://md.research.elamur.ai/free/en/papers/galley-2006-scalable-inference-training-context-rich/)** *(2006)* The paper extends the rule extraction of Galley et al. (2004). Instead of keeping one minimal derivation per sentence pair, it builds a forest of many derivations, so that larger rules with more syntactic context and alternative readings of unaligned words are all available. It puts probabilities on these multi-level… 2. **[What's in a translation rule?](https://md.research.elamur.ai/free/en/papers/galley-2004-what-s-translation-rule/)** *(2004)* The paper gives a formal meaning to word alignments between a parsed English sentence and its translation. ## Co-authors (7) - [Daniel Marcu](https://md.research.elamur.ai/free/en/authors/daniel-marcu/) ×2 - [Kevin Knight](https://md.research.elamur.ai/free/en/authors/kevin-knight/) ×2 - Ignacio Thayer - [Jonathan Graehl](https://md.research.elamur.ai/free/en/authors/jonathan-graehl/) - [Mark Hopkins](https://md.research.elamur.ai/free/en/authors/mark-hopkins/) - Steve DeNeefe - Wei Wang ## More papers in the library (13) Pages of the Research library: our summary, the ideas, references and who cites each. - [Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) — Pan Lu, Baolin Peng, Hao Cheng, et al. · 2023 - [Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback](https://md.research.elamur.ai/free/en/papers/peng-2023-check-facts-try-again-improving/) — Baolin Peng, Michel Galley, Pengcheng He, et al. · 2023 - [Instruction Tuning with GPT-4](https://md.research.elamur.ai/free/en/papers/peng-2023-instruction-tuning-gpt-4/) — Baolin Peng, Chunyuan Li, Pengcheng He, et al. · 2023 - [MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/) — Pan Lu, Hritik Bansal, Tony Xia, et al. · 2023 - [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/) — Yizhe Zhang, Siqi Sun, Michel Galley, et al. · 2019 - [A Diversity-Promoting Objective Function for Neural Conversation Models](https://md.research.elamur.ai/free/en/papers/li-2016-diversity-promoting-objective-function-neural/) — Jiwei Li, Michel Galley, Chris Brockett, et al. · 2016 - [A Persona-Based Neural Conversation Model](https://md.research.elamur.ai/free/en/papers/li-2016-persona-based-neural-conversation-model/) — Jiwei Li, Michel Galley, Chris Brockett, et al. · 2016 - [Deep Reinforcement Learning for Dialogue Generation](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/) — Jiwei Li, Will Monroe, Alan Ritter, et al. · 2016 - [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://md.research.elamur.ai/free/en/papers/sordoni-2015-neural-network-approach-context-sensitive/) — Alessandro Sordoni, Michel Galley, Michael Auli, et al. · 2015 - [A Simple and Effective Hierarchical Phrase Reordering Model](https://md.research.elamur.ai/free/en/papers/galley-2008-simple-effective-hierarchical-phrase-reordering/) — Michel Galley, Christopher D. Manning · 2008 - [Optimizing Chinese Word Segmentation for Machine Translation Performance](https://md.research.elamur.ai/free/en/papers/chang-2008-optimizing-chinese-word-segmentation-machine/) — Pi-Chuan Chang, Michel Galley, Christopher D. Manning · 2008 - [Identifying Agreement and Disagreement in Conversational Speech: Use of Bayesian Networks to Model Pragmatic Dependencies](https://md.research.elamur.ai/free/en/papers/galley-2004-identifying-agreement-disagreement-conversational-speech/) — Michel Galley, Kathleen McKeown, Julia Hirschberg, et al. · 2004 - [Discourse Segmentation of Multi-Party Conversation](https://md.research.elamur.ai/free/en/papers/galley-2003-discourse-segmentation-multi-party-conversation/) — Michel Galley, Kathleen R. McKeown, Eric Fosler-Lussier, et al. · 2003