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20242026
most citedCalibrating Large Language Models with Sample Consistency

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

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cs.CL2026

DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation

Bryan Li, William Walden, Yu Hou +6

Evaluation of long-form, citation-backed reports has lately received significant attention due to the wide-scale adoption of retrieval-augmented generation (RAG) systems. Core to m…

cs.CL20262 cited

Calibrating Large Language Models with Sample Consistency

Qing Lyu, Kumar Shridhar, Chaitanya Malaviya +6

Accurately gauging the confidence level of Large Language Models' (LLMs) predictions is pivotal for their reliable application. However, LLMs are often uncalibrated inherently and…

cs.CL2025

WHAT-IF: Exploring Branching Narratives by Meta-Prompting Large Language Models

Runsheng "Anson" Huang, Lara J. Martin, Chris Callison-Burch

WHAT-IF -- Writing a Hero's Alternate Timeline through Interactive Fiction -- is a system that uses zero-shot meta-prompting to create branching narratives from a prewritten story.…

cs.CL2024

PaCE: Parsimonious Concept Engineering for Large Language Models

Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan +4

Large Language Models (LLMs) are being used for a wide variety of tasks. While they are capable of generating human-like responses, they can also produce undesirable output includi…

cs.CL2024

Low-Resource Authorship Style Transfer: Can Non-Famous Authors Be Imitated?

Ajay Patel, Nicholas Andrews, Chris Callison-Burch

Authorship style transfer involves altering text to match the style of a target author whilst preserving the original meaning. Existing unsupervised approaches like STRAP have larg…

cs.CL2024

PDDLEGO: Iterative Planning in Textual Environments

Li Zhang, Peter Jansen, Tianyi Zhang +3

Planning in textual environments have been shown to be a long-standing challenge even for current models. A recent, promising line of work uses LLMs to generate a formal representa…