Papers with proxy tasks

5 papers
DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection (2024.findings-acl)

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Challenge: Large language models are limited by challenges in factuality and hallucinations to be directly employed off-the-shelf for judging the veracity of news articles.
Approach: They propose to integrate large language models into the news pipeline by generating news reactions and generating proxy tasks.
Outcome: The proposed model outperforms state-of-the-art baselines by 16.8% in macro f1-score on seven datasets with three LLMs.
Unveiling the Lexical Sensitivity of LLMs: Combinatorial Optimization for Prompt Enhancement (2024.emnlp-main)

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Challenge: Large language models (LLMs) demonstrate exceptional instruct-following ability to complete downstream tasks.
Approach: They propose a black-box combinatorial optimization framework that iteratively improves lexical choices in prompts by a search strategy related to word influence.
Outcome: The proposed framework recovers the model's ability to instruct-follow and solve downstream tasks even when the variations are imperceptible to humans.
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations (2021.emnlp-main)

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Challenge: Existing audio-language task-specific predictive approaches focus on building complicated late-fusion mechanisms.
Approach: They propose a cross-modal transformer for audio-and-language that learns inter-modal connections between audio and language through two proxy tasks on a large amount of audio- and-language pairs.
Outcome: The proposed model improves on multiple audio-and-language tasks and can be used in fine-tuning phase.
How coherent are neural models of coherence? (2020.coling-main)

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Challenge: Existing approaches to model coherence are limited to small newswire corpora . evaluators need to be trained on lexical and document levels to perform evaluations .
Approach: They propose four generic evaluation tasks that capture coherence-specific properties . they aim at capturing correct use of discourse connectives and lexical cohesion .
Outcome: The proposed tasks capture coherence-specific properties, including correct use of discourse connectives, lexical cohesion, temporal consistency among events and participants in a story.
Large-Scale Correlation Analysis of Automated Metrics for Topic Models (2023.acl-long)

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Challenge: Existing studies on topic models lack a correlation between automated coherence metrics and human judgement.
Approach: They propose a sampling approach to mine topics for metric evaluation and extend the analysis to measure topical differences between corpora.
Outcome: The proposed method extends to measure topical differences between corpora and human judgement by using extensive user study.

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