Are You Getting What You Pay For? Auditing Model Substitution in LLM APIs Paper • 2504.04715 • Published 10 days ago • 12
Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning Paper • 2407.04787 • Published Jul 5, 2024
JudgeBench: A Benchmark for Evaluating LLM-based Judges Paper • 2410.12784 • Published Oct 16, 2024 • 48
Differentially Private Synthetic Data via Foundation Model APIs 2: Text Paper • 2403.01749 • Published Mar 4, 2024
Effective and Efficient Federated Tree Learning on Hybrid Data Paper • 2310.11865 • Published Oct 18, 2023
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression Paper • 2403.15447 • Published Mar 18, 2024 • 16
Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation Paper • 2203.07687 • Published Mar 15, 2022
Protecting Language Generation Models via Invisible Watermarking Paper • 2302.03162 • Published Feb 6, 2023
Weak-to-Strong Jailbreaking on Large Language Models Paper • 2401.17256 • Published Jan 30, 2024 • 16
Agent Instructs Large Language Models to be General Zero-Shot Reasoners Paper • 2310.03710 • Published Oct 5, 2023 • 2
Agent Instructs Large Language Models to be General Zero-Shot Reasoners Paper • 2310.03710 • Published Oct 5, 2023 • 2
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models Paper • 2306.11698 • Published Jun 20, 2023 • 12
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models Paper • 2306.11698 • Published Jun 20, 2023 • 12
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models Paper • 2306.11698 • Published Jun 20, 2023 • 12