[2501.10868] Generating Structured Outputs from Language Models: Benchmark and Studies
![[2501.10868] Generating Structured Outputs from Language Models: Benchmark and Studies](https://i0.wp.com/arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png?w=1200&resize=1200,700&ssl=1 "[2501.10868] Generating Structured Outputs from Language Models: Benchmark and Studies"){kind=logo}
[Submitted on 18 Jan 2025 (v1), last revised 10 Feb 2025 (this version, v2)] View a PDF of the paper ...
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Proposing Several Tasks on Explainable Natural Language Inference
[Submitted on 15 Nov 2023 (v1), last revised 6 Feb 2025 (this version, v2)] View a PDF of the paper ...
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Adaptive Attention Sparsity with Hierarchical Top-$p$ Pruning
[Submitted on 4 Feb 2025 (v1), last revised 6 Feb 2025 (this version, v2)] View a PDF of the paper ...
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A Fine-grained Metric for Video Question Answering Data Quality Evaluation
[Submitted on 11 Nov 2024 (v1), last revised 6 Feb 2025 (this version, v3)] View a PDF of the paper ...
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Combining Base and Instruction-Tuned Language Models for Better Synthetic Data Generation
[Submitted on 3 Feb 2025 (v1), last revised 5 Feb 2025 (this version, v2)] View a PDF of the paper ...
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Rule-Guided Retrieval-Augmented Generation with Language Models for Question Answering
[Submitted on 15 Oct 2024 (v1), last revised 5 Feb 2025 (this version, v2)] View a PDF of the paper ...
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An Integrated Toolkit for Evaluating Jailbreak Attempts Against Large Language Models
[Submitted on 13 Jun 2024 (v1), last revised 4 Feb 2025 (this version, v2)] View a PDF of the paper ...
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Exploring the Role of Punctuation in Semantic Processing
[Submitted on 10 Jan 2025 (v1), last revised 2 Feb 2025 (this version, v3)] View a PDF of the paper ...
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[2501.07927] Gandalf the Red: Adaptive Security for LLMs
[Submitted on 14 Jan 2025 (v1), last revised 2 Feb 2025 (this version, v2)] Authors:Niklas Pfister, Václav Volhejn, Manuel Knott, ...
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Language Bias in Self-Supervised Learning For Automatic Speech Recognition
arXiv:2501.19321v1 Announce Type: cross Abstract: Self-supervised learning (SSL) is used in deep learning to train on large datasets without the ...
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