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Found 5 papers, 0 papers with code
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Also, we show that compared to natural language, pseudocode can better guide the reasoning of LMs, even though they are trained to follow natural language instructions.
Pearl: A Review-driven Persona-Knowledge Grounded Conversational Recommendation Dataset
Our experimental results demonstrate that utterances in PEARL include more specific user preferences, show expertise in the target domain, and provide recommendations more relevant to the dialogue context than those in prior datasets.
Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning
Towards this goal, we propose to mitigate the loss of knowledge from the interference among the different knowledge sources, by developing a modular variant of the knowledge aggregation as a new zero-shot commonsense reasoning framework.
Dual Task Framework for Improving Persona-grounded Dialogue Dataset
This paper introduces a simple yet effective data-centric approach for the task of improving persona-conditioned dialogue agents.
TrustAL: Trustworthy Active Learning using Knowledge Distillation
A traditional view of data acquisition is that, through iterations, knowledge from human labels and models is implicitly distilled to monotonically increase the accuracy and label consistency.
