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Found 5 papers, 4 papers with code
External Knowledge Selection with Weighted Negative Sampling in Knowledge-grounded Task-oriented Dialogue Systems
In the experiment, we investigate the effect of weighted negative sampling, post-training, and style transfer.
Instruction Matters, a Simple yet Effective Task Selection Approach in Instruction Tuning for Specific Tasks
Instruction tuning has shown its ability to not only enhance zero-shot generalization across various tasks but also its effectiveness in improving the performance of specific tasks.
TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Language Models (LMs) become outdated as the world changes; they often fail to perform tasks requiring recent factual information which was absent or different during training, a phenomenon called temporal misalignment.
Towards Continual Knowledge Learning of Language Models
By highlighting the critical causes of knowledge forgetting, we show that CKL is a challenging and important problem that helps us better understand and train ever-changing LMs.
Fine-grained Post-training for Improving Retrieval-based Dialogue Systems
During the multi-turn response selection, BERT focuses on training the relationship between the context with multiple utterances and the response.
Ranked #1 on
Conversational Response Selection
on RRS
