11 citations · 24 across the 33 of their papers we have counts for
6 papers · 1 filter
EvoPool: Evolutionary Programmatic Annotation for Label-Efficient Specialized Supervision
Tianyi Xu, Yaolun Zhang, Xuan Ouyang +1
Large language models excel at general tasks but underperform smaller supervised models in specialized, high-stakes domains where training labels are costly. We address this regime…
Speculative Pipeline Decoding: Higher-Accuracy Drafting with Hidden Latency via Pipeline Parallelism
Yijiong Yu, Huazheng Wang, Shuai Yuan +2
Speculative Decoding (SD) accelerates low-concurrency LLM inference with a draft-then-verify paradigm. Mainstream methods, however, rely on multi-token prediction, which incurs com…
SWAA: Sliding Window Attention Adaptation for Efficient and Quality Preserving Long Context Processing
Yijiong Yu, Jiale Liu, Qingyun Wu +2
The quadratic complexity of self attention in Transformer based LLMs renders long context inference prohibitively expensive. While Sliding Window Attention (SWA), the simplest spar…
Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at Scale
Jiale Liu, Yifan Zeng, Shaokun Zhang +5
LLM-based optimization has shown remarkable potential in enhancing agentic systems. However, the conventional approach of prompting LLM optimizer with the whole training trajectori…
Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models
Huazheng Wang, Yongcheng Jing, Haifeng Sun +4
In this paper, we investigate knowledge forgetting in large language models with a focus on its generalisation, ensuring that models forget not only specific training samples but a…
Memory-Augmented Agent Training for Business Document Understanding
Jiale Liu, Yifan Zeng, Malte Højmark-Bertelsen +3
Traditional enterprises face significant challenges in processing business documents, where tasks like extracting transport references from invoices remain largely manual despite t…