53 citations
- Microsoft (United States)US4 papers
- Carnegie Mellon UniversityUS3 papers
- Allen InstituteUS1 paper
- Allergan (India)IN1 paper
- Amazon (Germany)DE1 paper
- California Southern UniversityUS1 paper
- Central South UniversityCN1 paper
- Chinese Academy of SciencesCN1 paper
- Drexel UniversityUS1 paper
- Indian Institute of Technology HyderabadIN1 paper
- Indian Institute of Technology KharagpurIN1 paper
- Institute of SoftwareCN1 paper
Showing cs.LGShow all
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cs.LG2026
DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections
Haebin Shin, Lei Ji, Xiao Liu +4
As numerous instruction-tuning datasets continue to emerge, dynamically balancing and optimizing their mixtures has become a critical challenge. To address this, we propose Dynamix…
cs.LG2026★ 1 cited
RetroInfer: A Vector Storage Engine for Scalable Long-Context LLM Inference
Yaoqi Chen, Jinkai Zhang, Baotong Lu +16
Recent large language models (LLMs) are rapidly extending their context windows, yet inference throughput lags due to increasing GPU memory and bandwidth demands. This is because t…
cs.LG2026
SLM Finetuning for Natural Language to Domain Specific Code Generation in Production
Renjini R. Nair, Damian K. Kowalczyk, Marco Gaudesi +1
Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficult to meet with large models.…