3 papers
cs.AI2026
IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs
Songlin Bai, Xintong Wang, Linlin Yu +12
In industrial procurement, an LLM answer is useful only if it survives a standards check: recommended material must match operating condition, every parameter must respect a regula…
cs.IR2026
Thinking Broad, Acting Fast: Latent Reasoning Distillation from Multi-Perspective Chain-of-Thought for E-Commerce Relevance
Baopu Qiu, Hao Chen, Yuanrong Wu +4
Effective relevance modeling is crucial for e-commerce search, as it aligns search results with user intent and enhances customer experience. Recent work has leveraged large langua…
cs.CL2024
Self-Evolution Knowledge Distillation for LLM-based Machine Translation
Yuncheng Song, Liang Ding, Changtong Zan +1
Knowledge distillation (KD) has shown great promise in transferring knowledge from larger teacher models to smaller student models. However, existing KD strategies for large langua…