71 citations · 253 across the 31 of their papers we have counts for
6 papers · 1 filter
A Symbolic Adversarial Learning Framework for Evolving Fake News Generation and Detection
Chong Tian, Qirong Ho, Xiuying Chen
Rapid LLM advancements heighten fake news risks by enabling the automatic generation of increasingly sophisticated misinformation. Previous detection methods, including fine-tuned…
How Does Controllability Emerge In Language Models During Pretraining?
Jianshu She, Xinyue Li, Eric Xing +2
Language models can be steered by modifying their internal representations to control concepts such as emotion, style, or truthfulness in generation. However, the conditions for an…
Learning In Chaos: Efficient Autoscaling and Self-Healing for Multi-Party Distributed Training
Wenjiao Feng, Rongxing Xiao, Zonghang Li +6
Node and link churn in multi-party, cross-region clusters over wide-area networks (WANs) often disrupts distributed training. However, checkpoint-based recovery and cloud-centric a…
Token Level Routing Inference System for Edge Devices
Jianshu She, Wenhao Zheng, Zhengzhong Liu +4
The computational complexity of large language model (LLM) inference significantly constrains their deployment efficiency on edge devices. In contrast, small language models offer…
Prima.cpp: Fast 30-70B LLM Inference on Heterogeneous and Low-Resource Home Clusters
Zonghang Li, Tao Li, Wenjiao Feng +8
On-device inference offers privacy, offline use, and instant response, but consumer hardware restricts large language models (LLMs) to low throughput and capability. To overcome th…
Hawkeye:Efficient Reasoning with Model Collaboration
Jianshu She, Zhuohao Li, Zhemin Huang +4
Chain-of-Thought (CoT) reasoning has demonstrated remarkable effectiveness in enhancing the reasoning abilities of large language models (LLMs). However, its efficiency remains a c…