Tootfinder

Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets
Lei Hsiung, Tianyu Pang, Yung-Chen Tang, Linyue Song, Tsung-Yi Ho, Pin-Yu Chen, Yaoqing Yang
https://arxiv.org/abs/2506.05346

Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets
Recent advancements in large language models (LLMs) have underscored their vulnerability to safety alignment jailbreaks, particularly when subjected to downstream fine-tuning. However, existing mitigation strategies primarily focus on reactively addressing jailbreak incidents after safety guardrails have been compromised, removing harmful gradients during fine-tuning, or continuously reinforcing safety alignment throughout fine-tuning. As such, they tend to overlook a critical upstream factor: …

Buyer With Ties to Chinese Communist Party Got V.I.P. Treatment at Trump Crypto Dinner (New York Times)
https://www.nytimes.com/2025/06/06/us/politics/trump-crypto-dinner-china-he-tianying.html
http://www.memeorandum.com/250606/p144#a250606p144

Para los regalones mšs metaleros también tenemos lanzamientos musicales. «God Of Angels Trust» de los daneses Volbeat.
#Volbeat

This https://arxiv.org/abs/2506.02308 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

MINT: Multimodal Instruction Tuning with Multimodal Interaction Grouping
Recent advances in multimodal foundation models have achieved state-of-the-art performance across a range of tasks. These breakthroughs are largely driven by new pre-training paradigms that leverage large-scale, unlabeled multimodal data, followed by instruction fine-tuning on curated labeled datasets and high-quality prompts. While there is growing interest in scaling instruction fine-tuning to ever-larger datasets in both quantity and scale, our findings reveal that simply increasing the numb…

The Chinese Pulsar Timing Array data release I. Single pulsar noise analysis
Siyuan Chen, Heng Xu, Yanjun Guo, Bojun Wang, R. Nicolas Caballero, Jinchen Jiang, Jiangwei Xu, Zihan Xue, Kejia Lee, Jianping Yuan, Yonghua Xu, Jingbo Wang, Longfei Hao, Jintao Luo, Jinlin Han, Peng Jiang, Zhiqiang Shen, Min Wang, Na Wang, Renxin Xu, Xiangping Wu, Lei Qian, Xin Guan, Menglin Huang, Chun Sun, Yan Zhu

The Chinese Pulsar Timing Array data release I. Single pulsar noise analysis
The Chinese Pulsar Timing Array (CPTA) has collected observations from 57 millisecond pulsars using the Five-hundred-meter Aperture Spherical Radio Telescope (FAST) for close to three years, for the purpose of searching for gravitational waves (GWs). To robustly search for ultra-low-frequency GWs, pulsar timing arrays (PTAs) need to use models to describe the noise from the individual pulsars. We report on the results from the single pulsar noise analysis of the CPTA data release I (DR1). Conve…

This https://arxiv.org/abs/2410.00023 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Self-Tuning Spectral Clustering for Speaker Diarization
Spectral clustering has proven effective in grouping speech representations for speaker diarization tasks, although post-processing the affinity matrix remains difficult due to the need for careful tuning before constructing the Laplacian. In this study, we present a novel pruning algorithm to create a sparse affinity matrix called spectral clustering on p-neighborhood retained affinity matrix (SC-pNA). Our method improves on node-specific fixed neighbor selection by allowing a variable number …

This https://arxiv.org/abs/2505.08502 has been replaced.
initial toot: https://mastoxiv.page/@a…

Demonstration of Advanced Timing Schemes in Time-Resolved X-ray Diffraction Measurements
We present time-resolved X-ray diffraction measurements using advanced timing schemes that provide high temporal resolution while also maintaining a high flux in the X-ray probe beam. The method employs patterned probe pulse sequences that are generated with the WaveGate solid-state pulse picker. We demonstrate the feasibility of our method at two different beamlines on millisecond and microsecond timescales.

Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning
Hasin Us Sami, Swapneel Sen, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy, Basak Guler
https://arxiv.org/abs/2506.04453

Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning
Federated learning (FL) allows multiple data-owners to collaboratively train machine learning models by exchanging local gradients, while keeping their private data on-device. To simultaneously enhance privacy and training efficiency, recently parameter-efficient fine-tuning (PEFT) of large-scale pretrained models has gained substantial attention in FL. While keeping a pretrained (backbone) model frozen, each user fine-tunes only a few lightweight modules to be used in conjunction, to fit speci…

VisCoder: Fine-Tuning LLMs for Executable Python Visualization Code Generation
Yuansheng Ni, Ping Nie, Kai Zou, Xiang Yue, Wenhu Chen
https://arxiv.org/abs/2506.03930

VisCoder: Fine-Tuning LLMs for Executable Python Visualization Code Generation
Large language models (LLMs) often struggle with visualization tasks like plotting diagrams, charts, where success depends on both code correctness and visual semantics. Existing instruction-tuning datasets lack execution-grounded supervision and offer limited support for iterative code correction, resulting in fragile and unreliable plot generation. We present VisCode-200K, a large-scale instruction tuning dataset for Python-based visualization and self-correction. It contains over 200K exampl…

«More» Lo Nuevo de Pulp
https://open.spotify.com/album/4et2xBFMKmsaWQPjlKTbG6
¡Es hoy! 🤩
Después de casi ¼ de siglo hoy tenemos un nuevo disco de estudio de Pulp, una de las mšs icónicas bandas del britpop.
@…