The Impact of Inference Acceleration on Bias of LLMs
Fuente:
arXiv
Guardado en:
| Autores principales: | Kirsten, Elisabeth, Habernal, Ivan, Nanda, Vedant, Zafar, Muhammad Bilal |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs)
por: Neumann, Anna, et al.
Publicado: (2025)
por: Neumann, Anna, et al.
Publicado: (2025)
Private Language Models via Truncated Laplacian Mechanism
por: Huang, Tianhao, et al.
Publicado: (2024)
por: Huang, Tianhao, et al.
Publicado: (2024)
Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning
por: Minder, Julian, et al.
Publicado: (2025)
por: Minder, Julian, et al.
Publicado: (2025)
MANATEE: Inference-Time Lightweight Diffusion Based Safety Defense for LLMs
por: Kan, Chun Yan Ryan, et al.
Publicado: (2026)
por: Kan, Chun Yan Ryan, et al.
Publicado: (2026)
Relative Bias: A Comparative Framework for Quantifying Bias in LLMs
por: Arbabi, Alireza, et al.
Publicado: (2025)
por: Arbabi, Alireza, et al.
Publicado: (2025)
Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts
por: Mujahid, Zain Muhammad, et al.
Publicado: (2025)
por: Mujahid, Zain Muhammad, et al.
Publicado: (2025)
What's the plan? Metrics for implicit planning in LLMs and their application to rhyme generation and question answering
por: Maar, Jim, et al.
Publicado: (2026)
por: Maar, Jim, et al.
Publicado: (2026)
Censored LLMs as a Natural Testbed for Secret Knowledge Elicitation
por: Casademunt, Helena, et al.
Publicado: (2026)
por: Casademunt, Helena, et al.
Publicado: (2026)
Cloning Ideology and Style using Deep Learning
por: Beg, Omer, et al.
Publicado: (2022)
por: Beg, Omer, et al.
Publicado: (2022)
Lawma: The Power of Specialization for Legal Annotation
por: Dominguez-Olmedo, Ricardo, et al.
Publicado: (2024)
por: Dominguez-Olmedo, Ricardo, et al.
Publicado: (2024)
Building Production-Ready Probes For Gemini
por: Kramár, János, et al.
Publicado: (2026)
por: Kramár, János, et al.
Publicado: (2026)
Can LLMs Explain Themselves Counterfactually?
por: Dehghanighobadi, Zahra, et al.
Publicado: (2025)
por: Dehghanighobadi, Zahra, et al.
Publicado: (2025)
The Remarkable Robustness of LLMs: Stages of Inference?
por: Lad, Vedang, et al.
Publicado: (2024)
por: Lad, Vedang, et al.
Publicado: (2024)
Differentially-private text generation degrades output language quality
por: Çano, Erion, et al.
Publicado: (2025)
por: Çano, Erion, et al.
Publicado: (2025)
AGR: Age Group fairness Reward for Bias Mitigation in LLMs
por: Cao, Shuirong, et al.
Publicado: (2024)
por: Cao, Shuirong, et al.
Publicado: (2024)
Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
por: Siddique, Zara, et al.
Publicado: (2025)
por: Siddique, Zara, et al.
Publicado: (2025)
Explorations of Self-Repair in Language Models
por: Rushing, Cody, et al.
Publicado: (2024)
por: Rushing, Cody, et al.
Publicado: (2024)
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
por: Zhang, Fred, et al.
Publicado: (2023)
por: Zhang, Fred, et al.
Publicado: (2023)
Accelerated AI Inference via Dynamic Execution Methods
por: Barad, Haim, et al.
Publicado: (2024)
por: Barad, Haim, et al.
Publicado: (2024)
Accelerating Transformer Inference for Translation via Parallel Decoding
por: Santilli, Andrea, et al.
Publicado: (2023)
por: Santilli, Andrea, et al.
Publicado: (2023)
Not All Layers of LLMs Are Necessary During Inference
por: Fan, Siqi, et al.
Publicado: (2024)
por: Fan, Siqi, et al.
Publicado: (2024)
Does Differential Privacy Impact Bias in Pretrained NLP Models?
por: Islam, Md. Khairul, et al.
Publicado: (2024)
por: Islam, Md. Khairul, et al.
Publicado: (2024)
Bias Similarity Measurement: A Black-Box Audit of Fairness Across LLMs
por: Jeong, Hyejun, et al.
Publicado: (2024)
por: Jeong, Hyejun, et al.
Publicado: (2024)
Chain-of-Thought Reasoning In The Wild Is Not Always Faithful
por: Arcuschin, Iván, et al.
Publicado: (2025)
por: Arcuschin, Iván, et al.
Publicado: (2025)
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
por: Wen, Zhuofan, et al.
Publicado: (2024)
por: Wen, Zhuofan, et al.
Publicado: (2024)
Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
por: Timor, Nadav, et al.
Publicado: (2025)
por: Timor, Nadav, et al.
Publicado: (2025)
Position-Aware Parameter Efficient Fine-Tuning Approach for Reducing Positional Bias in LLMs
por: Zhang, Zheng, et al.
Publicado: (2024)
por: Zhang, Zheng, et al.
Publicado: (2024)
Transparent Screening for LLM Inference and Training Impacts
por: Pachot, Arnault, et al.
Publicado: (2026)
por: Pachot, Arnault, et al.
Publicado: (2026)
When Bias Pretends to Be Truth: How Spurious Correlations Undermine Hallucination Detection in LLMs
por: Wang, Shaowen, et al.
Publicado: (2025)
por: Wang, Shaowen, et al.
Publicado: (2025)
Investigating Bias: A Multilingual Pipeline for Generating, Solving, and Evaluating Math Problems with LLMs
por: Mahran, Mariam, et al.
Publicado: (2025)
por: Mahran, Mariam, et al.
Publicado: (2025)
Nudging: Inference-time Alignment of LLMs via Guided Decoding
por: Fei, Yu, et al.
Publicado: (2024)
por: Fei, Yu, et al.
Publicado: (2024)
GLASS: Global-Local Aggregation for Inference-time Sparsification of LLMs
por: Sattarifard, Amirmohsen, et al.
Publicado: (2025)
por: Sattarifard, Amirmohsen, et al.
Publicado: (2025)
Accelerating Prefilling for Long-Context LLMs via Sparse Pattern Sharing
por: Peng, Dan, et al.
Publicado: (2025)
por: Peng, Dan, et al.
Publicado: (2025)
Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis
por: Wei, Anjiang, et al.
Publicado: (2025)
por: Wei, Anjiang, et al.
Publicado: (2025)
Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge
por: Shen, Xuan, et al.
Publicado: (2023)
por: Shen, Xuan, et al.
Publicado: (2023)
Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps
por: Waldendorf, Jonas, et al.
Publicado: (2026)
por: Waldendorf, Jonas, et al.
Publicado: (2026)
Exploring the Hidden Capacity of LLMs for One-Step Text Generation
por: Mezentsev, Gleb, et al.
Publicado: (2025)
por: Mezentsev, Gleb, et al.
Publicado: (2025)
Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
por: Le, Qi, et al.
Publicado: (2025)
por: Le, Qi, et al.
Publicado: (2025)
Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs
por: Laine, Rudolf, et al.
Publicado: (2024)
por: Laine, Rudolf, et al.
Publicado: (2024)
ProxySPEX: Inference-Efficient Interpretability via Sparse Feature Interactions in LLMs
por: Butler, Landon, et al.
Publicado: (2025)
por: Butler, Landon, et al.
Publicado: (2025)
Ejemplares similares
-
Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs)
por: Neumann, Anna, et al.
Publicado: (2025) -
Private Language Models via Truncated Laplacian Mechanism
por: Huang, Tianhao, et al.
Publicado: (2024) -
Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning
por: Minder, Julian, et al.
Publicado: (2025) -
MANATEE: Inference-Time Lightweight Diffusion Based Safety Defense for LLMs
por: Kan, Chun Yan Ryan, et al.
Publicado: (2026) -
Relative Bias: A Comparative Framework for Quantifying Bias in LLMs
por: Arbabi, Alireza, et al.
Publicado: (2025)