ASAP-Bilkent/fake-privacy-finetuning-llms: v1
Fuente:
Zenodo
Saved in:
| Main Authors: | Masoud Poorghaffar Aghdam, lmj4869, Sinem Sav |
|---|---|
| Format: | Recurso digital |
| Published: |
Zenodo
2025
|
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data
by: Akkus, Atilla, et al.
Published: (2024)
by: Akkus, Atilla, et al.
Published: (2024)
Bridging Local and Federated Data Normalization in Federated Learning: A Privacy-Preserving Approach
by: Coşğun, Melih, et al.
Published: (2025)
by: Coşğun, Melih, et al.
Published: (2025)
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study
by: Mitic, Natalija, et al.
Published: (2024)
by: Mitic, Natalija, et al.
Published: (2024)
A Taxonomy of Attacks and Defenses in Split Learning
by: Shabbir, Aqsa, et al.
Published: (2025)
by: Shabbir, Aqsa, et al.
Published: (2025)
anguyen8/vision-llms-are-blind: official
by: Pooyan R, et al.
Published: (2026)
by: Pooyan R, et al.
Published: (2026)
A Report on the llms evaluating the high school questions
by: Jiawei, Zhu, et al.
Published: (2025)
by: Jiawei, Zhu, et al.
Published: (2025)
CURE: Privacy-Preserving Split Learning Done Right
by: Kanpak, Halil Ibrahim, et al.
Published: (2024)
by: Kanpak, Halil Ibrahim, et al.
Published: (2024)
SERSEM: Selective Entropy-Weighted Scoring for Membership Inference in Code Language Models
by: Dikici, Kıvanç Kuzey, et al.
Published: (2026)
by: Dikici, Kıvanç Kuzey, et al.
Published: (2026)
ASAP Emergency Practices
by: Zoppi, Ivano
Published: (2025)
by: Zoppi, Ivano
Published: (2025)
Does Cultural Fit Predict Well‐Adapted Personality? A Cross‐Cultural Comparison Between Turkey and Germany
by: Seher Sav, et al.
Published: (2025)
by: Seher Sav, et al.
Published: (2025)
ASAP Educational Programme: Handbook
by: Sanna, Stefano, et al.
Published: (2025)
by: Sanna, Stefano, et al.
Published: (2025)
compIAM-ConvTDF-vocals-finetune
by: Schweinitz, Serafin, et al.
Published: (2025)
by: Schweinitz, Serafin, et al.
Published: (2025)
ASAP Field Research Dataset: Czechia
by: Divjak, Marko, et al.
Published: (2025)
by: Divjak, Marko, et al.
Published: (2025)
ASAP: Attention Sink Anchored Pruning
by: Lee, Jaehyuk, et al.
Published: (2026)
by: Lee, Jaehyuk, et al.
Published: (2026)
Schemora: schema matching via multi-stage recommendation and metadata enrichment using off-the-shelf llms
by: Gungor, Osman Erman, et al.
Published: (2025)
by: Gungor, Osman Erman, et al.
Published: (2025)
PreFT: Prefill-only finetuning for efficient inference
by: Lanpouthakoun, Andrew, et al.
Published: (2026)
by: Lanpouthakoun, Andrew, et al.
Published: (2026)
Low-rank finetuning for LLMs: A fairness perspective
by: Das, Saswat, et al.
Published: (2024)
by: Das, Saswat, et al.
Published: (2024)
ASAP Desk Research Country Report: Italy
by: Giordano, Patrizia, et al.
Published: (2024)
by: Giordano, Patrizia, et al.
Published: (2024)
Meat Speciation via Deployable Atmospheric Solid Analysis Probe Mass Spectrometry (ASAP‐MS) Using Prototype RADIAN‐ASAP
by: Vanshni Vekereya, et al.
Published: (2026)
by: Vanshni Vekereya, et al.
Published: (2026)
Generalizing to any diverse distribution: uniformity, gentle finetuning and rebalancing
by: Loukas, Andreas, et al.
Published: (2024)
by: Loukas, Andreas, et al.
Published: (2024)
sam-llm: interpretable lane change trajectoryprediction via parametric finetuning
by: Cao, Zhuo, et al.
Published: (2025)
by: Cao, Zhuo, et al.
Published: (2025)
Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs
by: Betley, Jan, et al.
Published: (2025)
by: Betley, Jan, et al.
Published: (2025)
For-Value: Efficient Forward-Only Data Valuation for finetuning LLMs and VLMs
by: Deng, Wenlong, et al.
Published: (2025)
by: Deng, Wenlong, et al.
Published: (2025)
Low-resource finetuning of foundation models beats state-of-the-art in histopathology
by: Roth, Benedikt, et al.
Published: (2024)
by: Roth, Benedikt, et al.
Published: (2024)
ReMix: Reinforcement routing for mixtures of LoRAs in LLM finetuning
by: Qiu, Ruizhong, et al.
Published: (2026)
by: Qiu, Ruizhong, et al.
Published: (2026)
REZE: Representation Regularization for Domain-adaptive Text Embedding Pre-finetuning
by: Lee, Seungmin, et al.
Published: (2026)
by: Lee, Seungmin, et al.
Published: (2026)
Badllama 3: removing safety finetuning from Llama 3 in minutes
by: Volkov, Dmitrii
Published: (2024)
by: Volkov, Dmitrii
Published: (2024)
ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization
by: Fang, Han, et al.
Published: (2025)
by: Fang, Han, et al.
Published: (2025)
ASAP: Attention-Shift-Aware Pruning for Efficient LVLM Inference
by: Pathak, Surendra, et al.
Published: (2026)
by: Pathak, Surendra, et al.
Published: (2026)
fake_churn_data
by: Nikfar, Armaghan
Published: (2025)
by: Nikfar, Armaghan
Published: (2025)
Contesting fake news
by: Rehsmann, Daniel, et al.
Published: (2025)
by: Rehsmann, Daniel, et al.
Published: (2025)
On the generalization of language models from in-context learning and finetuning: a controlled study
by: Lampinen, Andrew K., et al.
Published: (2025)
by: Lampinen, Andrew K., et al.
Published: (2025)
RL-finetuning LLMs from on- and off-policy data with a single algorithm
by: Tang, Yunhao, et al.
Published: (2025)
by: Tang, Yunhao, et al.
Published: (2025)
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuse
by: Lippl, Samuel, et al.
Published: (2023)
by: Lippl, Samuel, et al.
Published: (2023)
Keep your hormones in check: microRNA 394 finetunes brassinosteroid signalling
by: Martin Balcerowicz
Published: (2024)
by: Martin Balcerowicz
Published: (2024)
BadGPT-4o: stripping safety finetuning from GPT models
by: Krupkina, Ekaterina, et al.
Published: (2024)
by: Krupkina, Ekaterina, et al.
Published: (2024)
Regular $(2+1)$-dimensional spatially homogeneous $α'$-corrected BTZ-like black hole in string theory
by: Naderi, F., et al.
Published: (2023)
by: Naderi, F., et al.
Published: (2023)
Quasinormal modes of three $(2+1)$-dimensional black holes in string theory, conformal gravity, and Hu-Sawicki $F(R)$ theory via the Heun function
by: Naderi, F., et al.
Published: (2024)
by: Naderi, F., et al.
Published: (2024)
ASAP-MO:Advanced Situational Awareness and Perception for Mission-critical Operations
by: Vannini, Veronica, et al.
Published: (2025)
by: Vannini, Veronica, et al.
Published: (2025)
ASAP: Amortized Doubly-Stochastic Attention via Sliced Dual Projection
by: Tran, Huy, et al.
Published: (2026)
by: Tran, Huy, et al.
Published: (2026)
Similar Items
-
Generated Data with Fake Privacy: Hidden Dangers of Fine-tuning Large Language Models on Generated Data
by: Akkus, Atilla, et al.
Published: (2024) -
Bridging Local and Federated Data Normalization in Federated Learning: A Privacy-Preserving Approach
by: Coşğun, Melih, et al.
Published: (2025) -
How to Privately Tune Hyperparameters in Federated Learning? Insights from a Benchmark Study
by: Mitic, Natalija, et al.
Published: (2024) -
A Taxonomy of Attacks and Defenses in Split Learning
by: Shabbir, Aqsa, et al.
Published: (2025) -
anguyen8/vision-llms-are-blind: official
by: Pooyan R, et al.
Published: (2026)