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On Context Utilization in Summarization with Large Language Models
Mathieu Ravaut, Aixin Sun, Nancy F. Chen +1
Large language models (LLMs) excel in abstractive summarization tasks, delivering fluent and pertinent summaries. Recent advancements have extended their capabilities to handle lon…
Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution
Xinze Li, Yixin Cao, Liangming Pan +2
Although achieving great success, Large Language Models (LLMs) usually suffer from unreliable hallucinations. Although language attribution can be a potential solution, there are n…
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Yu Cheng, Yunzhu Pan, Jiaqi Zhang +3
Recommender systems (RS) have achieved significant success by leveraging explicit identification (ID) features. However, the full potential of content features, especially the pure…
FLM-101B: An Open LLM and How to Train It with $100K Budget
Xiang Li, Yiqun Yao, Xin Jiang +10
Large language models (LLMs) are considered important approaches towards foundational machine intelligence, achieving remarkable success in Natural Language Processing and multimod…
Research Explosion: More Effort to Climb onto Shoulders of the Giant
Guoxiu He, Aixin Sun, Wei Lu
Fast-growing scientific publications present challenges to the scientific community. In this paper, we describe their implications to researchers. As references form explicit found…
Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting
Chen Chen, Yufei Wang, Aixin Sun +2
Knowledge Graph Completion (KGC) often requires both KG structural and textual information to be effective. Pre-trained Language Models (PLMs) have been used to learn the textual i…