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Found 12 papers, 7 papers with code
Towards Truthful Multilingual Large Language Models: Benchmarking and Alignment Strategies
In the era of large language models (LLMs), building multilingual large language models (MLLMs) that can serve users worldwide holds great significance.
Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration
The proliferation of Large Language Models (LLMs) has led to an influx of AI-generated content (AIGC) on the internet, transforming the corpus of Information Retrieval (IR) systems from solely human-written to a coexistence with LLM-generated content.
RA-ISF: Learning to Answer and Understand from Retrieval Augmentation via Iterative Self-Feedback
Large language models (LLMs) demonstrate exceptional performance in numerous tasks but still heavily rely on knowledge stored in their parameters.
SPA: Towards A Computational Friendly Cloud-Base and On-Devices Collaboration Seq2seq Personalized Generation with Casual Inference
Large language models(LLMs) have shown its outperforming ability on various tasks and question answering.
ERA-CoT: Improving Chain-of-Thought through Entity Relationship Analysis
Large language models (LLMs) have achieved commendable accomplishments in various natural language processing tasks.
MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models
Fine-tuning is often necessary to enhance the adaptability of Large Language Models (LLM) to downstream tasks.
Neural Retrievers are Biased Towards LLM-Generated Content
Surprisingly, our findings indicate that neural retrieval models tend to rank LLM-generated documents higher.
TableQAKit: A Comprehensive and Practical Toolkit for Table-based Question Answering
Table-based question answering (TableQA) is an important task in natural language processing, which requires comprehending tables and employing various reasoning ways to answer the questions.
HRoT: Hybrid prompt strategy and Retrieval of Thought for Table-Text Hybrid Question Answering
Answering numerical questions over hybrid contents from the given tables and text(TextTableQA) is a challenging task.
Modality Unifying Network for Visible-Infrared Person Re-Identification
Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-modality discrepancies and intra-class variations.
MMHQA-ICL: Multimodal In-context Learning for Hybrid Question Answering over Text, Tables and Images
Most importantly, we propose a Type-specific In-context Learning Strategy for MMHQA, enabling LLMs to leverage their powerful performance in this task.
Advancing Topic Segmentation and Outline Generation in Chinese Texts: The Paragraph-level Topic Representation, Corpus, and Benchmark
Topic segmentation and outline generation strive to divide a document into coherent topic sections and generate corresponding subheadings, unveiling the discourse topic structure of a document.
