Available here. Some that look especially interesting:
- A Discriminative Global Training Algorithm for Statistical MT (Tillmann and Zhang)
- Semi-Supervised Conditional Random Fields for Improved Sequence Segmentation and Labeling (Jiao, Wang, Lee, Greiner and Schuurmans)
- An Iterative Implicit Feedback Approach to Personalized Search (Lv, Sun, Zhang, Nie, Chen and Zhang)
- Training Conditional Random Fields with Multivariate Evaluation Measures (Suzuki, McDermott and Isozaki)
- Integrating Syntactic Priming into an Incremental Probabilistic Parser, with an Application to Psycholinguistic Modeling (Dubey, Keller and Sturt)
- Robust PCFG-Based Generation using Automatically Acquired LFG Approximations (Cahill and van Genabith)
- Exploiting Syntactic Patterns as Clues in Zero-Anaphora Resolution (Iida)
- An End-to-End Discriminative Approach to Machine Translation (Liang, Bouchard-Cote, Taskar and Klein)
2 comments:
Liang's paper is very neat--finally, someone has applied structured classification directly to MT!
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