45 citations · 96 across the 11 of their papers we have counts for
8 papers · 1 filter
Reasoning Models are Test Exploiters: Rethinking Multiple-Choice
Narun Raman, Taylor Lundy, Kevin Leyton-Brown
When evaluating Large Language Models (LLMs) in question answering domains, it is common to ask the model to choose among a fixed set of choices (so-called multiple-choice question…
STEER-ME: Assessing the Microeconomic Reasoning of Large Language Models
Narun Raman, Taylor Lundy, Thiago Amin +2
How should one judge whether a given large language model (LLM) can reliably perform economic reasoning? Most existing LLM benchmarks focus on specific applications and fail to pre…
What Can Natural Language Processing Do for Peer Review?
Ilia Kuznetsov, Osama Mohammed Afzal, Koen Dercksen +21
The number of scientific articles produced every year is growing rapidly. Providing quality control over them is crucial for scientists and, ultimately, for the public good. In mod…
STEER: Assessing the Economic Rationality of Large Language Models
Narun Raman, Taylor Lundy, Samuel Amouyal +3
There is increasing interest in using LLMs as decision-making "agents." Doing so includes many degrees of freedom: which model should be used; how should it be prompted; should it…
Generating Benchmarks for Factuality Evaluation of Language Models
Dor Muhlgay, Ori Ram, Inbal Magar +7
Before deploying a language model (LM) within a given domain, it is important to measure its tendency to generate factually incorrect information in that domain. Existing methods f…
In-Context Retrieval-Augmented Language Models
Ori Ram, Yoav Levine, Itay Dalmedigos +4
Retrieval-Augmented Language Modeling (RALM) methods, which condition a language model (LM) on relevant documents from a grounding corpus during generation, were shown to significa…
Parallel Context Windows for Large Language Models
Nir Ratner, Yoav Levine, Yonatan Belinkov +7
When applied to processing long text, Large Language Models (LLMs) are limited by their context window. Existing efforts to address this limitation involve training specialized arc…
MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning
Ehud Karpas, Omri Abend, Yonatan Belinkov +14
Huge language models (LMs) have ushered in a new era for AI, serving as a gateway to natural-language-based knowledge tasks. Although an essential element of modern AI, LMs are als…