695 citations · 2.7k across the 76 of their papers we have counts for
46 papers · 1 filter
Characterizing Mamba's Selective Memory using Auto-Encoders
Tamanna Hossain, Robert L. Logan, Ganesh Jagadeesan +3
State space models (SSMs) are a promising alternative to transformers for language modeling because they use fixed memory during inference. However, this fixed memory usage require…
Parallel Token Prediction for Language Models
Felix Draxler, Justus Will, Farrin Marouf Sofian +3
Autoregressive decoding in language models is inherently slow, generating only one token per forward pass. We propose Parallel Token Prediction (PTP), a general-purpose framework f…
Leveraging In-Context Learning for Language Model Agents
Shivanshu Gupta, Sameer Singh, Ashish Sabharwal +2
In-context learning (ICL) with dynamically selected demonstrations combines the flexibility of prompting large language models (LLMs) with the ability to leverage training data to…
Nudging: Inference-time Alignment of LLMs via Guided Decoding
Yu Fei, Yasaman Razeghi, Sameer Singh
Large language models (LLMs) require alignment to effectively and safely follow user instructions. This process necessitates training an aligned version for every base model, resul…
Perceptions of Linguistic Uncertainty by Language Models and Humans
Catarina G Belem, Markelle Kelly, Mark Steyvers +2
_Uncertainty expressions_ such as "probably" or "highly unlikely" are pervasive in human language. While prior work has established that there is population-level agreement in term…
Are Models Biased on Text without Gender-related Language?
Catarina G Belém, Preethi Seshadri, Yasaman Razeghi +1
Gender bias research has been pivotal in revealing undesirable behaviors in large language models, exposing serious gender stereotypes associated with occupations, and emotions. A…