PACE pipelines an LLM's thinking with a robot's action execution and adapts reasoning token budgets to action time windows, cutting thinking time 6.9x and hiding 66.8% of thinking inside execution.
Language Cognition and Language Computation -- Human and Machine Language Understanding
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Language understanding is a key scientific issue in the fields of cognitive and computer science. However, the two disciplines differ substantially in the specific research questions. Cognitive science focuses on analyzing the specific mechanism of the brain and investigating the brain's response to language; few studies have examined the brain's language system as a whole. By contrast, computer scientists focus on the efficiency of practical applications when choosing research questions but may ignore the most essential laws of language. Given these differences, can a combination of the disciplines offer new insights for building intelligent language models and studying language cognitive mechanisms? In the following text, we first review the research questions, history, and methods of language understanding in cognitive and computer science, focusing on the current progress and challenges. We then compare and contrast the research of language understanding in cognitive and computer sciences. Finally, we review existing work that combines insights from language cognition and language computation and offer prospects for future development trends.
citation-role summary
citation-polarity summary
fields
cs.RO 1years
2026 1verdicts
CONDITIONAL 1roles
contradiction 1polarities
contest 1representative citing papers
citing papers explorer
-
PACE: Adaptive Budget Allocation for Time-Efficient Embodied Planning
PACE pipelines an LLM's thinking with a robot's action execution and adapts reasoning token budgets to action time windows, cutting thinking time 6.9x and hiding 66.8% of thinking inside execution.