activity
20232026
most citedPointwise Mutual Information as a Performance Gauge for Retrieval-Augmented Generation

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Ensembling Language Models with Sequential Monte Carlo

Robin Shing Moon Chan, Tianyu Liu, Samuel Kiegeland +5

Practitioners have access to an abundance of language models and prompting strategies for solving many language modeling tasks; yet prior work shows that modeling performance is hi…

cs.CL2026

Transducing Language Models

Vésteinn Snæbjarnarson, Samuel Kiegeland, Tianyu Liu +3

Modern language models define distributions over strings, but downstream tasks often require different output formats. For instance, a model that generates byte-pair strings does n…

cs.CL2026

Post-Training Language Models for Crosslingual Consistency

Tianyu Liu, Jirui Qi, Mrinmaya Sachan +3

Language models often respond inconsistently to translation-equivalent prompts across languages, undermining the reliability of multilingual systems. To quantify this, we give an i…

cs.CL2024★ 1 cited

Pointwise Mutual Information as a Performance Gauge for Retrieval-Augmented Generation

Tianyu Liu, Jirui Qi, Paul He +3

Recent work suggests that large language models enhanced with retrieval-augmented generation are easily influenced by the order, in which the retrieved documents are presented to t…

cs.CL2024

Efficiently Computing Susceptibility to Context in Language Models

Tianyu Liu, Kevin Du, Mrinmaya Sachan +1

One strength of modern language models is their ability to incorporate information from a user-input context when answering queries. However, they are not equally sensitive to the…

cs.CL2024

A Probability--Quality Trade-off in Aligned Language Models and its Relation to Sampling Adaptors

Naaman Tan, Josef Valvoda, Tianyu Liu +4

The relationship between the quality of a string, as judged by a human reader, and its probability, under a language model undergirds the development of better…

cs.CL2023★ 1 cited

Formal Aspects of Language Modeling

Ryan Cotterell, Anej Svete, Clara Meister +2

Large language models have become one of the most commonly deployed NLP inventions. In the past half-decade, their integration into core natural language processing tools has drama…