32 citations · 64 across the 26 of their papers we have counts for
5 papers · 1 filter
: Unifying Generation and Self-Verification for Parallel Reasoners
Harman Singh, Xiuyu Li, Kusha Sareen +14
Test-time scaling for complex reasoning tasks shows that leveraging inference-time compute, by methods such as independently sampling and aggregating multiple solutions, results in…
Distilling Token-Trained Models into Byte-Level Models
Zishuo Bao, Jiaqi Leng, Junxiong Wang +2
Byte Language Models (BLMs) have emerged as a promising direction for scaling language models beyond tokenization. However, existing BLMs typically require training from scratch on…
Understanding and Improving Length Generalization in Hierarchical Sparse Attention Models
Jiaqi Leng, Xiang Hu, Junxiong Wang +3
Effectively processing long contexts is a critical challenge for language models. While standard Transformers are limited by quadratic complexity and poor length extrapolation, alt…
StatEval: A Comprehensive Benchmark for Large Language Models in Statistics
Yuchen Lu, Run Yang, Yichen Zhang +6
Despite rapid advances in large language models (LLMs), statistical reasoning remains underrepresented in existing LLM benchmarks, which often do not reflect the layered, proof-dri…
Feeding LLM Annotations to BERT Classifiers at Your Own Risk
Yucheng Lu, Kazimier Smith
Using LLM-generated labels to fine-tune smaller encoder-only models for text classification has gained popularity in various settings. While this approach may be justified in simpl…