Lin Qu
8 papers · 2022–2026 · 3 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌍
Conference Polyglot · Bronze
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(20)
👥
Mega-Team · Squad
Venues
Top co-authors
Research topics
Artificial Intelligence
(4)
Deep Learning
(4)
Machine Learning
(4)
Application Areas
(4)
Computer Science
(3)
Core AI
(3)
Systems
(3)
Learning Types · Deep Learning
(2)
Optimization & Theory · Deep Learning
(2)
Optimization & Theory · Machine Learning
(2)
Natural Language Processing
(1)
Reinforcement Learning
(1)
Learning Paradigms
(1)
Learning Types · Machine Learning
(1)
Methods
(1)
Keywords
large language model
(3)
reinforcement learning
(2)
domain adaptation
(2)
distributed training
(2)
gradient aggregation
(1)
model serving
(1)
resource allocation
(1)
parameter server
(1)
asynchronous training
(1)
straggler mitigation
(1)
scaling law
(1)
mixture of expert
(1)
pipeline parallelism
(1)
continual pre-training
(1)
downstream performance
(1)
mixture ratio
(1)
cross-domain generalization
(1)
head-of-line blocking
(1)
gpu utilization
(1)
cluster scheduling
(1)
Papers
Attack of the Bubbles: Straggler-Resilient Pipeline Parallelism for Large Model Training
NSDI 2026
RollArt: Disaggregated Multi-Task Agentic RL Training at Scale
OSDI 2026
RollPacker: Taming Long-Tail Rollouts for RL Post-Training with Tail Batching
NSDI 2026
Weave: Efficient Co-Scheduling for Disaggregated RL Post-Training
OSDI 2026
GPU-Disaggregated Serving for Deep Learning Recommendation Models at Scale
NSDI 2025
D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models
NeurIPS 2024
DDK: Distilling Domain Knowledge for Efficient Large Language Models
NeurIPS 2024
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Models
NeurIPS 2022