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Found 9 papers, 7 papers with code
Quantifying the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
Robustness has become a critical attribute for the deployment of RAG systems in real-world applications.
MuDAF: Long-Context Multi-Document Attention Focusing through Contrastive Learning on Attention Heads
Large Language Models (LLMs) frequently show distracted attention due to irrelevant information in the input, which severely impairs their long-context capabilities.
Fostering Natural Conversation in Large Language Models with NICO: a Natural Interactive COnversation dataset
Benefiting from diverse instruction datasets, contemporary Large Language Models (LLMs) perform effectively as AI assistants in collaborating with humans.
Multi-level Contrastive Learning for Script-based Character Understanding
In this work, we tackle the scenario of understanding characters in scripts, which aims to learn the characters' personalities and identities from their utterances.
A New Benchmark and Reverse Validation Method for Passage-level Hallucination Detection
Contrasting previous studies of zero-resource hallucination detection, our method and benchmark concentrate on passage-level detection instead of sentence-level.
A New Dataset and Empirical Study for Sentence Simplification in Chinese
Sentence Simplification is a valuable technique that can benefit language learners and children a lot.
Human-like Summarization Evaluation with ChatGPT
Evaluating text summarization is a challenging problem, and existing evaluation metrics are far from satisfactory.
LAD-RCNN:A Powerful Tool for Livestock Face Detection and Normalization
However, there is no study on normalizing of the animal face image with arbitrary directions.
Fine-grained Contrastive Learning for Definition Generation
Recently, pre-trained transformer-based models have achieved great success in the task of definition generation (DG).
