2 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
The Depth Ceiling: On the Limits of Large Language Models in Discovering Latent Planning
Yi Xu, Philipp Jettkant, Laura Ruis
The viability of chain-of-thought (CoT) monitoring hinges on models being unable to reason effectively in their latent representations. Yet little is known about the limits of such…
AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs
Nicholas E. Corrado, Julian Katz-Samuels, Adithya Devraj +6
When aligning large language models (LLMs), their performance on various tasks (such as being helpful, harmless, and honest) depends heavily on the composition of their training da…
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
Yilun Jin, Zheng Li, Chenwei Zhang +19
Online shopping is a complex multi-task, few-shot learning problem with a wide and evolving range of entities, relations, and tasks. However, existing models and benchmarks are com…
Evolutionary Contrastive Distillation for Language Model Alignment
Julian Katz-Samuels, Zheng Li, Hyokun Yun +5
The ability of large language models (LLMs) to execute complex instructions is essential for their real-world applications. However, several recent studies indicate that LLMs strug…