2 citations · 4 across the 14 of their papers we have counts for
5 papers · 1 filter
FramingQA: Does the Question Shape the Answer? Measuring the Compositional Framing Effect
Hazel H. Kim, Andrew M. Bean, Guilherme Affonso Ferreira de Camargo +10
We introduce FramingQA, a benchmark that measures the model sensitivity to question framing across law, medicine, finance, and robotic simulations. Large language models (LLMs) oft…
A Systematic Evaluation of Cross-Lingual Consistency Enhancement Methods in Multilingual Language Models
Jirui Qi, Mingyang Wang, Hinrich Schütze +2
Multilingual language models often produce inconsistent answers to semantically equivalent questions across languages, motivating methods to improve cross-lingual consistency (CLC)…
A Target-Centric Survey of Quantization-Aware Training
Jiamin Song, Mengjie Zhao, Zijing Wang +6
The rapid development of LLMs incurs prohibitive memory footprints and intensive computational demands. Quantization-Aware Training (QAT) techniques have emerged as a promising sol…
MemWM: Memory-Augmented Text-Based World Model
Yujun Wang, Tao Zhang, Jinhe Bi +9
World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent next-state predictions can sti…
GLUScope: A Tool for Analyzing GLU Neurons in Transformer Language Models
Sebastian Gerstner, Hinrich Schütze, Leonor Veloso
We present **GLUScope**, an open-source resource for analyzing neurons in Transformer-based language models (LMs), intended for interpretability researchers. We focus on the now-st…