9 citations · 20 across the 5 of their papers we have counts for
6 papers
Co-Linguistics: AI-augmented Theory Construction in Linguistics
Emmanuel Chemla, Benjamin Spector, Alexandros Kalomoiros +1
LLMs have been studied in recent linguistics as potential models of humans' linguistic abilities. Here we discuss an entirely different use of AI, namely as a co-scientist, to help…
Explaining vague language
Paul Égré, Benjamin Spector
Why is language vague? Vagueness may be explained and rationalized if it can be shown that vague language is more useful to speaker and hearer than precise language. In a well-know…
Accelerating LLM Inference with Staged Speculative Decoding
Benjamin Spector, Chris Re
Recent advances with large language models (LLM) illustrate their diverse capabilities. We propose a novel algorithm, staged speculative decoding, to accelerate LLM inference in sm…
Exhaustivity and anti-exhaustivity in the RSA framework: Testing the effect of prior beliefs
Alexandre Cremers, Ethan G. Wilcox, Benjamin Spector
During communication, the interpretation of utterances is sensitive to a listener's probabilistic prior beliefs, something which is captured by one currently influential model of p…
Bounding the Last Mile: Efficient Learned String Indexing
Benjamin Spector, Andreas Kipf, Kapil Vaidya +3
We introduce the RadixStringSpline (RSS) learned index structure for efficiently indexing strings. RSS is a tree of radix splines each indexing a fixed number of bytes. RSS approac…
On the Optimality of Vagueness: "Around", "Between", and the Gricean Maxims
Paul Egré, Benjamin Spector, Adèle Mortier +1
Why is ordinary language vague? We argue that in contexts in which a cooperative speaker is not perfectly informed about the world, the use of vague expressions can offer an optima…