The Politics of Language Choice: How the Russian-Ukrainian War Influences Ukrainians' Language Use on Twitter. (arXiv:2305.02770v3 [cs.CY] UPDATED)
CCpdf: Building a High Quality Corpus for Visually Rich Documents from Web Crawl Data. (arXiv:2304.14953v2 [cs.CL] UPDATED)
A logical word embedding for learning grammar. (arXiv:2304.14590v2 [cs.CL] UPDATED)
NAIST-SIC-Aligned: Automatically-Aligned English-Japanese Simultaneous Interpretation Corpus. (arXiv:2304.11766v3 [cs.CL] UPDATED)
Joint Repetition Suppression and Content Moderation of Large Language Models. (arXiv:2304.10611v2 [cs.CL] UPDATED)
Graph2topic: an opensource topic modeling framework based on sentence embedding and community detection. (arXiv:2304.06653v3 [cs.CL] UPDATED)
PDFVQA: A New Dataset for Real-World VQA on PDF Documents. (arXiv:2304.06447v5 [cs.CV] UPDATED)
oBERTa: Improving Sparse Transfer Learning via improved initialization, distillation, and pruning regimes. (arXiv:2303.17612v3 [cs.CL] UPDATED)
Aligning Language Models with Preferences through f-divergence Minimization. (arXiv:2302.08215v2 [cs.CL] UPDATED)
DP-BART for Privatized Text Rewriting under Local Differential Privacy. (arXiv:2302.07636v2 [cs.CR] UPDATED)
Large Language Models Can Be Easily Distracted by Irrelevant Context. (arXiv:2302.00093v3 [cs.CL] UPDATED)
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning. (arXiv:2301.12132v2 [cs.CL] UPDATED)
How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech. (arXiv:2301.11462v2 [cs.CL] UPDATED)
A Watermark for Large Language Models. (arXiv:2301.10226v3 [cs.LG] UPDATED)
NarrowBERT: Accelerating Masked Language Model Pretraining and Inference. (arXiv:2301.04761v2 [cs.CL] UPDATED)
DISCO: Distilling Counterfactuals with Large Language Models. (arXiv:2212.10534v3 [cs.CL] UPDATED)
Benchmarking Spatial Relationships in Text-to-Image Generation. (arXiv:2212.10015v2 [cs.CV] UPDATED)
DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation. (arXiv:2212.08724v3 [cs.CL] UPDATED)
Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation. (arXiv:2212.07981v2 [cs.CL] UPDATED)
Can In-context Learners Learn a Reasoning Concept from Demonstrations?. (arXiv:2212.01692v3 [cs.CL] UPDATED)
All recent Computation and Language articles on arXiv.org for the Fediverse
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