Recurrent Linguistic Domain Papers?

[Nici Schraudolph]

Jeff Elman has trained a simple recurrent prediction network on a corpus
of sentences with embedded clauses produced by a recursive grammar.  The
net was required to remember noun/verb agreement across the embedded
clauses; its capacity to do so showed limits similar to those of human
linguistic capability: namely, performance degraded after about three
levels of embedding, with center embeddings more adversely affected than
tail recursions.

These findings are reported in his tech report "Representation and
Structure in Connectionist Models" (CRL TR 8903), available from the
Center for Research in Language, UCSD, LA Jolla, CA 92093-0108
(e-mail: jan at amos.ucsd.edu).

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Nici Schraudolph, C-014                nschraudolph at ucsd.edu
University of California, San Diego    nschraudolph at ucsd.bitnet
La Jolla, CA 92093                     ...!ucsd!nschraudolph