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Found 5 papers, 2 papers with code
Memory-Augmented Generative Adversarial Transformers
Conversational AI systems that rely on Large Language Models, like Transformers, have difficulty interweaving external data (like facts) with the language they generate.
Communication Drives the Emergence of Language Universals in Neural Agents: Evidence from the Word-order/Case-marking Trade-off
Artificial learners often behave differently from human learners in the context of neural agent-based simulations of language emergence and change.
The Effect of Efficient Messaging and Input Variability on Neural-Agent Iterated Language Learning
Natural languages display a trade-off among different strategies to convey syntactic structure, such as word order or inflection.
Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering
In this work, we train a GPT-2 language model to generate three distractors for a given question and text context, using the RACE dataset.
Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective
Developing successful sign language recognition, generation, and translation systems requires expertise in a wide range of fields, including computer vision, computer graphics, natural language processing, human-computer interaction, linguistics, and Deaf culture.
Cultural Vocal Bursts Intensity Prediction
Sign Language Recognition
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