Many studies have shown that attraction effects are consistently found for linguistic dependencies like subject-verb agreement, e.g., The key to the cabinets are on the table. However, not all dependencies are equally susceptible to attraction. A parade case involves reflexive-antecedent dependencies, which rarely show attraction effects. The contrast between agreement and reflexives with respe...

Research in language processing has established that semantic information can influence (a) online sentence interpretation when syntactic cues are indeterminate, and (b) offline judgments of syntactically unambiguous but semantically anomalous sentences. The question of whether semantic information can influence online sentence interpretation when semantic cues oppose unambiguous syntax remains...

A conventional path-based neural predictor (PBNP) achieves very high prediction accuracy, but its very deeply pipelined implementation makes it both a complex and power-intensive component. One of the major reasons for the large complexity and power is that for a history length of h, the PBNP must use h separately indexed SRAM arrays (or suffer from a very long update latency) organized in an h...

Appropriate and extensive taxon sampling is one of the most important determinants of accurate phylogenetic estimation. In addition, accuracy of inferences about evolutionary processes obtained from phylogenetic analyses is improved significantly by thorough taxon sampling efforts. Many recent efforts to improve phylogenetic estimates have focused instead on increasing sequence length or the nu...

Phylogenetic methods are key to providing models for how a given protein family evolved. However, these methods run into difficulties when sequence divergence is either too low or too high. Here, we provide a case study of Hox and ParaHox proteins so that additional insights can be gained using a new computational approach to help solve old classification problems. For two (Gsx and Cdx) out of ...

This paper presents a new method for branch prediction. The key idea is to use one of the simplest possible neural networks, the perceptron, as an alternative to the commonly used two-bit counters. Our predictor achieves increased accuracy by making use of long branch histories, which are possible because the hardware resources for our method scale linearly with the history length. By contrast,...