Test Dataset Accuracies for Pragmatic Language Emergence Models

A small dataset of 5.5 KB contains test accuracy results from a computational modeling study of pragmatic language emergence. The study, authored by Kristina Kobrock and shared on figshare in May 2026, models context-based and utility-based pragmatic reasoning in a multi-agent framework. Results show that languages emerging in a shared context become more efficient and ambiguous.

Use Cases

• Benchmarking pragmatic language emergence models based on reported test accuracies.
• Analyzing the efficiency tradeoff between speaker and listener utilities described in the study.
• Investigating the role of shared context in shaping emergent language and category systems.
• Comparing the effects of context-based versus utility-based pragmatics on linguistic efficiency.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• File size is precisely 5.5 KB, indicating a focused, non-bulky dataset.
• The study's methodology and theoretical framework (Rational Speech Acts) are explicitly described.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset's scope is limited to test accuracy results from a specific modeling experiment.

Provenance

Source

figshare

Collection Method

Results generated from a computational model of emergent communication.

Freshness

Last updated 2026-05-26 17:46:44; freshness should be verified.