Thank you for such an invitation. Let's see. Given the choice of a) reading through thousands of lines of code trying to figure out why the default behaviour performs considerably worse than merely selecting the most likely translation of each phrase or b) spending much less time implementing a simple system that does just that
which one would you do? For all know maybe I've already implemented such a system that does just that and not only that improves considerably on such a basic benchmark. But given that on this list we don't seem to be able to accept that there is a problem with the default behaviour of Moses I can only conclude that nobody would be interested in access to the code of such a system. James ________________________________________ From: amittai axelrod <amit...@umiacs.umd.edu> Sent: Friday, June 19, 2015 7:52 PM To: Read, James C; Lane Schwartz Cc: moses-support@mit.edu; Philipp Koehn Subject: Re: [Moses-support] Major bug found in Moses if we don't understand the problem, how can we possibly fix it? all the relevant code is open source. go for it! ~amittai On 6/19/15 12:49, Read, James C wrote: > So, all I did was filter out the less likely phrase pairs and the BLEU > score shot up. Was that such a stroke of genius? Was that not blindingly > obvious? > > > Your telling me that redesigning the search algorithm to prefer higher > scoring phrase pairs is all we need to do to get a best paper at ACL? > > > James > > > > ------------------------------------------------------------------------ > *From:* Lane Schwartz <dowob...@gmail.com> > *Sent:* Friday, June 19, 2015 7:40 PM > *To:* Read, James C > *Cc:* Philipp Koehn; Burger, John D.; moses-support@mit.edu > *Subject:* Re: [Moses-support] Major bug found in Moses > On Fri, Jun 19, 2015 at 11:28 AM, Read, James C <jcr...@essex.ac.uk > <mailto:jcr...@essex.ac.uk>> wrote: > > What I take issue with is the en-masse denial that there is a > problem with the system if it behaves in such a way with no LM + no > pruning and/or tuning. > > > There is no mass denial taking place. > > Regardless of whether or not you tune, the decoder will do its best to > find translations with the highest model score. That is the expected > behavior. > > What I have tried to tell you, and what other people have tried to tell > you, is that translations with high model scores are not necessarily > good translations. > > We all want our models to be such that high model scores correspond to > good translations, and that low model scores correspond with bad > translations. But unfortunately, our models do not innately have this > characteristic. We all know this. We also know a good way to deal with > this shortcoming, namely tuning. Tuning is the process by which we > attempt to ensure that high model scores correspond to high quality > translations, and that low model scores correspond to low quality > translations. > > If you can design models that naturally correspond with translation > quality without tuning, that's great. If you can do that, you've got a > great shot at winning a Best Paper award at ACL. > > In the meantime, you may want to consider an apology for your rude > behavior and unprofessional attitude. > > Goodbye. > Lane > > > > _______________________________________________ > Moses-support mailing list > Moses-support@mit.edu > http://mailman.mit.edu/mailman/listinfo/moses-support > _______________________________________________ Moses-support mailing list Moses-support@mit.edu http://mailman.mit.edu/mailman/listinfo/moses-support
