4 papers · 1 filter
Rho-1: Not All Tokens Are What You Need
Zhenghao Lin, Zhibin Gou, Yeyun Gong +8
Previous language model pre-training methods have uniformly applied a next-token prediction loss to all training tokens. Challenging this norm, we posit that "9l training". Our ini…
ERBench: An Entity-Relationship based Automatically Verifiable Hallucination Benchmark for Large Language Models
Jio Oh, Soyeon Kim, Junseok Seo +4
Large language models (LLMs) have achieved unprecedented performances in various applications, yet evaluating them is still challenging. Existing benchmarks are either manually con…
Dynamic Evaluation of Large Language Models by Meta Probing Agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao +2
Evaluation of large language models (LLMs) has raised great concerns in the community due to the issue of data contamination. Existing work designed evaluation protocols using well…
Supervised Knowledge Makes Large Language Models Better In-context Learners
Linyi Yang, Shuibai Zhang, Zhuohao Yu +8
Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded th…