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cs.CL2025
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Zhaolu Kang, Junhao Gong, Jiaxu Yan +15
Multimodal Large Language Models (MLLMs) have demonstrated significant potential to advance a broad range of domains. However, current benchmarks for evaluating MLLMs primarily emp…
cs.CL2024★ 1 cited
NutePrune: Efficient Progressive Pruning with Numerous Teachers for Large Language Models
Shengrui Li, Junzhe Chen, Xueting Han +1
The considerable size of Large Language Models (LLMs) presents notable deployment challenges, particularly on resource-constrained hardware. Structured pruning, offers an effective…