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cs.CL2024
LOGO -- Long cOntext aliGnment via efficient preference Optimization
Zecheng Tang, Zechen Sun, Juntao Li +2
Long-context models(LCMs) have shown great potential in processing long input sequences(even more than 100M tokens) conveniently and effectively. With significant progress, recent…
cs.CL2024
Unleashing LLM Reasoning Capability via Scalable Question Synthesis from Scratch
Yuyang Ding, Xinyu Shi, Xiaobo Liang +4
Improving the mathematical reasoning capabilities of Large Language Models (LLMs) is critical for advancing artificial intelligence. However, access to extensive, diverse, and high…
cs.CL2024
OpenBA-V2: Reaching 77.3% High Compression Ratio with Fast Multi-Stage Pruning
Dan Qiao, Yi Su, Pinzheng Wang +18
Large Language Models (LLMs) have played an important role in many fields due to their powerful capabilities.However, their massive number of parameters leads to high deployment re…