2 citations · 4 across the 14 of their papers we have counts for
8 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)…
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…
EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget
Liang Chen, Xueting Han, Qizhou Wang +4
Balancing exploration and exploitation remains a central challenge in reinforcement learning with verifiable rewards (RLVR) for large language models (LLMs). Current RLVR methods o…
SLAyiNG: A Diverse and Community-validated Dataset of Queer Slang
Leonor Veloso, Lea Hirlimann, Lucija Mihić Zidar +3
Queer vernacular is rarely studied in NLP, despite advancements in resources and evaluation for other sociolects and informal language. Because of this, NLP systems often process q…
A Recipe of Parallel Corpora Exploitation for Multilingual Large Language Models
Peiqin Lin, André F. T. Martins, Hinrich Schütze
Recent studies have highlighted the potential of exploiting parallel corpora to enhance multilingual large language models, improving performance in both bilingual tasks, e.g., mac…
BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models
Jacek Wiland, Max Ploner, Alan Akbik
Knowledge probing assesses to which degree a language model (LM) has successfully learned relational knowledge during pre-training. Probing is an inexpensive way to compare LMs of…
MorphPiece : A Linguistic Tokenizer for Large Language Models
Haris Jabbar
Tokenization is a critical part of modern NLP pipelines. However, contemporary tokenizers for Large Language Models are based on statistical analysis of text corpora, without much…