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20232026
most citedPRobELM: Plausibility Ranking Evaluation for Language Models

1 citations · 2 across the 17 of their papers we have counts for

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Showing 2024Show all

9 papers · 1 filter

cs.CL2024

Segment-Level Diffusion: A Framework for Controllable Long-Form Generation with Diffusion Language Models

Xiaochen Zhu, Georgi Karadzhov, Chenxi Whitehouse +1

Diffusion models have shown promise in text generation, but often struggle with generating long, coherent, and contextually accurate text. Token-level diffusion doesn't model word-…

cs.CV2024

Decompose and Leverage Preferences from Expert Models for Improving Trustworthiness of MLLMs

Rui Cao, Yuming Jiang, Michael Schlichtkrull +1

Multimodal Large Language Models (MLLMs) can enhance trustworthiness by aligning with human preferences. As human preference labeling is laborious, recent works employ evaluation m…

cs.CL2024

TabVer: Tabular Fact Verification with Natural Logic

Rami Aly, Andreas Vlachos

Fact verification on tabular evidence incentivises the use of symbolic reasoning models where a logical form is constructed (e.g. a LISP-style program), providing greater verifiabi…

cs.CL2024

Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking

Mubashara Akhtar, Michael Schlichtkrull, Andreas Vlachos

Current automated fact-checking (AFC) approaches typically evaluate evidence either implicitly via the predicted verdicts or through exact matches with predefined closed knowledge…

cs.CL2024

The Automated Verification of Textual Claims (AVeriTeC) Shared Task

Michael Schlichtkrull, Yulong Chen, Chenxi Whitehouse +9

The Automated Verification of Textual Claims (AVeriTeC) shared task asks participants to retrieve evidence and predict veracity for real-world claims checked by fact-checkers. Evid…

cs.CL2024

Zero-Shot Fact Verification via Natural Logic and Large Language Models

Marek Strong, Rami Aly, Andreas Vlachos

The recent development of fact verification systems with natural logic has enhanced their explainability by aligning claims with evidence through set-theoretic operators, providing…

cs.CL2024★ 1 cited

Document-level Claim Extraction and Decontextualisation for Fact-Checking

Zhenyun Deng, Michael Schlichtkrull, Andreas Vlachos

Selecting which claims to check is a time-consuming task for human fact-checkers, especially from documents consisting of multiple sentences and containing multiple claims. However…

cs.CL2024

Automated Focused Feedback Generation for Scientific Writing Assistance

Eric Chamoun, Michael Schlichktrull, Andreas Vlachos

Scientific writing is a challenging task, particularly for novice researchers who often rely on feedback from experienced peers. Recent work has primarily focused on improving surf…

cs.CL2024★ 1 cited

PRobELM: Plausibility Ranking Evaluation for Language Models

Zhangdie Yuan, Eric Chamoun, Rami Aly +2

This paper introduces PRobELM (Plausibility Ranking Evaluation for Language Models), a benchmark designed to assess language models' ability to discern more plausible from less pla…