1 citations · 3 across the 14 of their papers we have counts for
4 papers · 2 filters
The First ChineseBabyLM Challenge: training data-efficient and cognitively plausible language models for Chinese
Siyuan Song, Zhiheng Qian, Yunhao Zhang +11
This paper presents the first ChineseBabyLM Challenge, organized as part of NLPCC 2026. The challenge asked participants to train language models from scratch using no more than 10…
Prune, Interpret, Evaluate: A Cross-Layer Transcoder-Native Framework for Efficient Circuit Discovery via Feature Attribution
Qinhao Chen, Linyang He, Nima Mesgarani
Existing feature-interpretation pipelines typically operate on uniformly sampled units or exhaustive feature sets, incurring massive costs on units irrelevant to target behaviors.…
LiveMathematicianBench: A Live Benchmark for Research-Level Mathematical Reasoning with Proof Sketches
Linyang He, Qiyao Yu, Hanze Dong +5
Mathematical reasoning is a hallmark of human intelligence, and whether large language models (LLMs) can meaningfully perform it remains a central question in artificial intelligen…
LLMs Think with DAGs: Probing the Latent Graph Structure of Reasoning
Tianjun Zhong, Linyang He, Ziyang Li +1
Large language models often externalize reasoning as linear chains, but many reasoning problems can be more naturally modeled as directed acyclic graphs (DAGs), where intermediate…