6 citations · 18 across the 24 of their papers we have counts for
10 papers · 1 filter
KBAlign: Efficient Self Adaptation on Specific Knowledge Bases
Zheni Zeng, Yuxuan Chen, Shi Yu +7
Although retrieval-augmented generation (RAG) remains essential for knowledge-based question answering (KBQA), current paradigms face critical challenges under specific domains. Ex…
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Yuqi Luo, Chenyang Song, Xu Han +7
Activation sparsity denotes the existence of substantial weakly-contributed elements within activation outputs that can be eliminated, benefiting many important applications concer…
LLMMapReduce: Simplified Long-Sequence Processing using Large Language Models
Zihan Zhou, Chong Li, Xinyi Chen +11
Enlarging the context window of large language models (LLMs) has become a crucial research area, particularly for applications involving extremely long texts. In this work, we prop…
VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents
Shi Yu, Chaoyue Tang, Bokai Xu +8
Retrieval-augmented generation (RAG) is an effective technique that enables large language models (LLMs) to utilize external knowledge sources for generation. However, current RAG…
DeepNote: Note-Centric Deep Retrieval-Augmented Generation
Ruobing Wang, Qingfei Zhao, Yukun Yan +9
Retrieval-Augmented Generation (RAG) mitigates factual errors and hallucinations in Large Language Models (LLMs) for question-answering (QA) by incorporating external knowledge. Ho…
Stuffed Mamba: Oversized States Lead to the Inability to Forget
Yingfa Chen, Xinrong Zhang, Shengding Hu +3
Recent advancements in recurrent architectures, such as Mamba and RWKV, have showcased strong language capabilities. Unlike transformer-based models, these architectures encode all…
Locret: Enhancing Eviction in Long-Context LLM Inference with Trained Retaining Heads on Consumer-Grade Devices
Yuxiang Huang, Binhang Yuan, Xu Han +2
Scaling the input context length of a large language model (LLM) incurs a significant increase in computation cost and memory footprint to maintain the attention key-value (KV) cac…
From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents
Jifan Yu, Zheyuan Zhang, Daniel Zhang-li +30
Since the first instances of online education, where courses were uploaded to accessible and shared online platforms, this form of scaling the dissemination of human knowledge to r…
MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization
Zhiyu Yang, Zihan Zhou, Shuo Wang +10
Scientific data visualization plays a crucial role in research by enabling the direct display of complex information and assisting researchers in identifying implicit patterns. Des…
Unified View of Grokking, Double Descent and Emergent Abilities: A Perspective from Circuits Competition
Yufei Huang, Shengding Hu, Xu Han +2
Recent studies have uncovered intriguing phenomena in deep learning, such as grokking, double descent, and emergent abilities in large language models, which challenge human intuit…