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cs.CL2026
EoRA: Fine-tuning-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation
Shih-Yang Liu, Maksim Khadkevich, Nai Chit Fung +10
While post-training compression techniques effectively reduce the memory footprint, latency, and power consumption of Large Language Models (LLMs), they often result in noticeable…
cs.CL2025
OpusLM: A Family of Open Unified Speech Language Models
Jinchuan Tian, William Chen, Yifan Peng +9
This paper presents Open Unified Speech Language Models (OpusLMs), a family of open foundational speech language models (SpeechLMs) up to 7B. Initialized from decoder-only text lan…