Trading off Utility, Informativeness, and Complexity in Emergent Communication

Beyond linear regression: mapping models in cognitive neuroscience should align with research goals

Towards Human-Agent Communication via the Information Bottleneck Principle

Teasing apart models of pragmatics using optimal reference game design

The emergence of discrete and systematic communication in a continuous signal-meaning space

The evolution of color naming reflects pressure for efficiency: Evidence from the recent past

The forms and meanings of grammatical markers support efficient communication

Scalable pragmatic communication via self-supervision

Let's talk (efficiently) about us: Person systems achieve near-optimal compression

Empirical support for a Rate-Distortion account of pragmatic reasoning

Competition from novel features drives scalar inferences in reference games

Is it that simple? Linear mapping models in cognitive neuroscience

Probing artificial neural networks: insights from neuroscience

Cross­linguistic patterns in person systems reflect efficient coding

A Rate–Distortion view of human pragmatic reasoning

Bayesian Approaches to Color Category Learning

Cloze Distillation: Improving Neural Language Models with Human Next-Word Prediction

A Rate–Distortion view of human pragmatic reasoning

Toward human-like object naming in artificial neural systems

Emergence of pragmatic reasoning from least-effort optimization

Information-Theoretic Principles in the Evolution of Semantic Systems

Deterministic annealing and the evolution of Information Bottleneck representations

Evolution and efficiency in color naming: The case of Nafaanra

Semantic categories of artifacts and animals reflect efficient coding

Communicative need in color naming

Color naming reflects both perceptual structure and communicative need

Efficient compression in color naming and its evolution

Color naming reflects both perceptual structure and communicative need (earlier version)

Efficient human-like semantic representations via the Information Bottleneck principle

Efficient encoding of motion is mediated by gap junctions in the fly visual system

Early motion processing circuit uses gap junctions to achieve efficient stimuli encoding

Deep learning and the Information Bottleneck principle