1 citations · 1 across the 8 of their papers we have counts for
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MachineLearningLM: Scaling Many-shot In-context Learning via Continued Pretraining
Haoyu Dong, Pengkun Zhang, Mingzhe Lu +2
Large language models (LLMs) possess broad world knowledge and strong general-purpose reasoning ability, yet they struggle to learn from many in-context examples on standard machin…
Masked-and-Reordered Self-Supervision for Reinforcement Learning from Verifiable Rewards
Zhen Wang, Zhifeng Gao, Guolin Ke
Test-time scaling has been shown to substantially improve large language models' (LLMs) mathematical reasoning. However, for a large portion of mathematical corpora, especially the…
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Hengxing Cai, Xiaochen Cai, Junhan Chang +20
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of…
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Hengxing Cai, Xiaochen Cai, Shuwen Yang +14
In scientific research and its application, scientific literature analysis is crucial as it allows researchers to build on the work of others. However, the fast growth of scientifi…