papers

Publications (11)

cs.CL2022

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…

cs.CL2022

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…

cs.CL2025

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…

cs.CL2024

Just read twice: closing the recall gap for recurrent language models

Simran Arora, Aman Timalsina, Aaryan Singhal +6

Recurrent large language models that compete with Transformers in language modeling perplexity are emerging at a rapid rate (e.g., Mamba, RWKV). Excitingly, these architectures use…

cs.DB2021

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…

cs.LG2025

LoLCATs: On Low-Rank Linearizing of Large Language Models

Michael Zhang, Simran Arora, Rahul Chalamala +5

Recent works show we can linearize large language models (LLMs) -- swapping the quadratic attentions of popular Transformer-based LLMs with subquadratic analogs, such as linear att…