13 papers · 1 filter
WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment
Jiefu Ou, Arda Uzunoglu, Benjamin Van Durme +1
AI systems make decisions in physical environments through primitive actions or affordances that are accessed via API calls. While deploying AI agents in the real world involves nu…
Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data
Jingyu Zhang, Marc Marone, Tianjian Li +2
To trust the fluent generations of large language models (LLMs), humans must be able to verify their correctness against trusted, external sources. Recent efforts, such as providin…
Benchmarking Language Model Creativity: A Case Study on Code Generation
Yining Lu, Dixuan Wang, Tianjian Li +4
As LLMs become increasingly prevalent, it is interesting to consider how ``creative'' these models can be. From cognitive science, creativity consists of at least two key character…
DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation
Weiting Tan, Jingyu Zhang, Lingfeng Shen +2
Non-autoregressive Transformers (NATs) are recently applied in direct speech-to-speech translation systems, which convert speech across different languages without intermediate tex…
Core: Robust Factual Precision with Informative Sub-Claim Identification
Zhengping Jiang, Jingyu Zhang, Nathaniel Weir +6
Hallucinations pose a challenge to the application of large language models (LLMs) thereby motivating the development of metrics to evaluate factual precision. We observe that popu…
Insights into LLM Long-Context Failures: When Transformers Know but Don't Tell
Taiming Lu, Muhan Gao, Kuai Yu +2
Large Language Models (LLMs) exhibit positional bias, struggling to utilize information from the middle or end of long contexts. Our study explores LLMs' long-context reasoning by…