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Found 5 papers, 3 papers with code
One Shot Learning as Instruction Data Prospector for Large Language Models
Nuggets assesses the potential of individual instruction examples to act as effective one shot examples, thereby identifying those that can significantly enhance diverse task performance.
Marathon: A Race Through the Realm of Long Context with Large Language Models
Although there are currently many benchmarks available for evaluating the long context understanding and reasoning capability of large language models, with the expansion of the context window in these models, the existing long context benchmarks are no longer sufficient for evaluating the long context understanding and reasoning capability of large language models.
VDialogUE: A Unified Evaluation Benchmark for Visually-grounded Dialogue
Visually-grounded dialog systems, which integrate multiple modes of communication such as text and visual inputs, have become an increasingly popular area of investigation.
PaCE: Unified Multi-modal Dialogue Pre-training with Progressive and Compositional Experts
It utilizes a combination of several fundamental experts to accommodate multiple dialogue-related tasks and can be pre-trained using limited dialogue and extensive non-dialogue multi-modal data.
Ranked #1 on
Response Generation
on SIMMC2.0
Self-Distillation with Meta Learning for Knowledge Graph Completion
In this paper, we propose a selfdistillation framework with meta learning(MetaSD) for knowledge graph completion with dynamic pruning, which aims to learn compressed graph embeddings and tackle the longtail samples.
Ranked #4 on
Link Prediction
on FB15k-237
