4 citations · 13 across the 12 of their papers we have counts for
13 papers
PRiSM: Benchmarking Phone Realization in Speech Models
Shikhar Bharadwaj, Chin-Jou Li, Yoonjae Kim +13
Phone recognition (PR) serves as the atomic interface for language-agnostic modeling for cross-lingual speech processing and phonetic analysis. Despite prolonged efforts in develop…
Searching for the Most Human-like Emergent Language
Brendon Boldt, David Mortensen
In this paper, we design a signalling game-based emergent communication environment to generate state-of-the-art emergent languages in terms of similarity to human language. This i…
Morpheme Induction for Emergent Language
Brendon Boldt, David Mortensen
We introduce CSAR, an algorithm for inducing morphemes from emergent language corpora of parallel utterances and meanings. It is a greedy algorithm that (1) weights morphemes based…
XferBench: a Data-Driven Benchmark for Emergent Language
Brendon Boldt, David Mortensen
In this paper, we introduce a benchmark for evaluating the overall quality of emergent languages using data-driven methods. Specifically, we interpret the notion of the "quality" o…
A Review of the Applications of Deep Learning-Based Emergent Communication
Brendon Boldt, David Mortensen
Emergent communication, or emergent language, is the field of research which studies how human language-like communication systems emerge de novo in deep multi-agent reinforcement…
ELCC: the Emergent Language Corpus Collection
Brendon Boldt, David Mortensen
We introduce the Emergent Language Corpus Collection (ELCC): a collection of corpora generated from open source implementations of emergent communication systems across the literat…
Mathematically Modeling the Lexicon Entropy of Emergent Language
Brendon Boldt, David Mortensen
We formulate a stochastic process, FiLex, as a mathematical model of lexicon entropy in deep learning-based emergent language systems. Defining a model mathematically allows it to…
Recommendations for Systematic Research on Emergent Language
Brendon Boldt, David Mortensen
Emergent language is unique among fields within the discipline of machine learning for its open-endedness, not obviously presenting well-defined problems to be solved. As a result,…
Modeling Emergent Lexicon Formation with a Self-Reinforcing Stochastic Process
Brendon Boldt, David Mortensen
We introduce FiLex, a self-reinforcing stochastic process which models finite lexicons in emergent language experiments. The central property of FiLex is that it is a self-reinforc…
Case Study: Deontological Ethics in NLP
Shrimai Prabhumoye, Brendon Boldt, Ruslan Salakhutdinov +1
Recent work in natural language processing (NLP) has focused on ethical challenges such as understanding and mitigating bias in data and algorithms; identifying objectionable conte…
Detecting Compromised Implicit Association Test Results Using Supervised Learning
Brendon Boldt, Zack While, Eric Breimer
An implicit association test is a human psychological test used to measure subconscious associations. While widely recognized by psychologists as an effective tool in measuring att…
Using LSTMs to Model the Java Programming Language
Brendon Boldt
Recurrent neural networks (RNNs), specifically long-short term memory networks (LSTMs), can model natural language effectively. This research investigates the ability for these sam…
Precise but Natural Specification for Robot Tasks
Ivan Gavran, Brendon Boldt, Eva Darulova +1
We present Flipper, a natural language interface for describing high-level task specifications for robots that are compiled into robot actions. Flipper starts with a formal core la…