Library

TLDR: Extreme Summarization of Scientific Documents

We introduce TLDR generation, a new form of extreme summarization, for scientific papers. TLDR generation involves high source compression and requires expert background knowledge and understanding of complex domain-specific language. To facilitate study on this task, we introduce SciTLDR, a new multi-target dataset of 5.4K TLDRs over 3.2K papers. SciTLDR contains both author-written and expert…

cs.CL
Source

Paper

Similar papers

FlipGuard: Defending Preference Alignment against Update Regression with Constrained OptimizationMingye Zhu, Yi Liu, Quan Wang et al.2024 · Conference on Empirical Methods in Natural Language Processing · 2 citations In Library
Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMsQitao Tan, Xiaoying Song, Arman Akbari et al.2026 · arXiv.org · 1 citation In Library
TamperBench: A Systematic Benchmark for Fine-Tuning Attack Resistance in Safety-Aligned Open-Weight Language ModelsHamda Aden2026 · Zenodo (CERN European Organization for Nuclear Research) In Library
TamperBench: A Systematic Benchmark for Fine-Tuning Attack Resistance in Safety-Aligned Open-Weight Language ModelsHamda Aden2026 · Zenodo (CERN European Organization for Nuclear Research) In Library
Disentangled Safety Adapters Enable Efficient Guardrails and Flexible Inference-Time AlignmentK. Krishna, J. Y. Cheng, Charlie Maalouf et al.2025 · arXiv.org · 4 citations In Library
Beyond Surface Alignment: Rebuilding LLMs Safety Mechanism via Probabilistically Ablating Refusal DirectionYuanbo Xie, Yingjie Zhang, Tianyun Liu et al.2025 · arXiv (Cornell University) · 6 citations In Library
Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMsWaiman Si, Mingjie Li, Michael Backes et al.2026 · Annual Meeting of the Association for Computational Linguistics · 0 citations In Library
GR-SAP: Generative Replay for Safety Alignment Preservation during Fine-TuningZhouxiang Fang, Jiawei Zhou, Hanjie Chen2026 · arXiv.org · 0 citations In Library
FinHarmBench: Financial Jailbreak Benchmark and Unsupervised Safety Fine-Tuning via Refusal Steering DistillationYubin Choi, Yujin Yang, Subin Kim et al.2026 In Library
On the Safety of Graph Representation LearningXiaoguang Guo, Zehong Wang, Ziming Li et al.2026 · arXiv.org · 0 citations In Library
© 2026 NYSGPT2525 LLC