1 citations · 1 across the 8 of their papers we have counts for
9 papers
Evolving in Thought Space: Training a Small Model at Test Time Unlocks Better Discoveries
Chonghe Jiang, Ao Qu, Siyuan Liu +9
Open-ended scientific discovery often requires repeatedly proposing and evaluating candidate solutions. LLM-based systems can support this process by generating and refining execut…
SPADE: Self-Play in Adaptive Synthetic Executable Environments
Bo Liu, Simon Yu, Yiding Jiang +15
Continuous self-improvement requires an ever-expanding pool of self-generated, diverse, adaptive goals. For language agents, existing training environment pools (hand-curated, stat…
The Diminishing Returns of Early-Exit Decoding in Modern LLMs
Rui Wei, Rui Du, Hanfei Yu +4
In Large Language Model (LLM) inference, early-exit refers to stopping computation at an intermediate layer once the prediction is sufficiently confident, thereby reducing latency…
MoEless: Efficient MoE LLM Serving with Serverless Experts
Hanfei Yu, Bei Ouyang, Shwai He +2
Large Language Models (LLMs) increasingly adopt Mixture-of-Experts (MoE) architectures to scale efficiently under stringent resource constraints. However, MoE's sparse activation c…
RLHFless: Serverless Computing for Efficient RLHF
Rui Wei, Hanfei Yu, Shubham Jain +5
Reinforcement Learning from Human Feedback (RLHF) has been widely applied to Large Language Model (LLM) post-training to align model outputs with human preferences. Recent models,…
ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving
Yifan Sui, Hao Wang, Hanfei Yu +5
Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This makes it attractive for serving l…
Taming Latency-Memory Trade-Off in MoE-Based LLM Serving via Fine-Grained Expert Offloading
Hanfei Yu, Xingqi Cui, Hong Zhang +1
Large Language Models (LLMs) have gained immense success in revolutionizing various applications, including content generation, search and recommendation, and AI-assisted operation…
Accelerating Serverless Computing by Harvesting Idle Resources
Hanfei Yu, Hao Wang, Jian Li +2
Serverless computing automates fine-grained resource scaling and simplifies the development and deployment of online services with stateless functions. However, it is still non-tri…
Leveraging GPT-2 for Classifying Spam Reviews with Limited Labeled Data via Adversarial Training
Athirai A. Irissappane, Hanfei Yu, Yankun Shen +2
Online reviews are a vital source of information when purchasing a service or a product. Opinion spammers manipulate these reviews, deliberately altering the overall perception of…