Image de couverture de livre

The Hidden Costs of Translation Accuracy: Distillation, Quantization, and Environmental Impact

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Vijay, Dhaathri, Vadapalli, Anandaswarup
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

An investigation of phrase break prediction in an End-to-End TTS system
par: Vadapalli, Anandaswarup
Publié: (2023)

CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
par: Halder, Deepon, et autres
Publié: (2025)

Reinforcement Learning vs. Distillation: Understanding Accuracy and Capability in LLM Reasoning
par: Kim, Minwu, et autres
Publié: (2025)

Efficient Technical Term Translation: A Knowledge Distillation Approach for Parenthetical Terminology Translation
par: Myung, Jiyoon, et autres
Publié: (2024)

A Study on Hidden Layer Distillation for Large Language Model Pre-Training
par: Guigon, Maxime, et autres
Publié: (2026)

Towards Understanding and Improving Knowledge Distillation for Neural Machine Translation
par: Zhang, Songming, et autres
Publié: (2023)

Automatic Transmission for LLM Tiers: Optimizing Cost and Accuracy in Large Language Models
par: Na, Injae, et autres
Publié: (2025)

Dual-Head Reasoning Distillation: Improving Classifier Accuracy with Train-Time-Only Reasoning
par: Xu, Jillian, et autres
Publié: (2025)

TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation
par: Sun, Lin, et autres
Publié: (2025)

PMMT: Preference Alignment in Multilingual Machine Translation via LLM Distillation
par: Sun, Shuqiao, et autres
Publié: (2024)

Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High Accuracy and Low Cost
par: Belyi, Masha, et autres
Publié: (2024)

How and Where to Translate? The Impact of Translation Strategies in Cross-lingual LLM Prompting
par: Gupta, Aman, et autres
Publié: (2025)

To Think or Not to Think: The Hidden Cost of Meta-Training with Excessive CoT Examples
par: Kothapalli, Vignesh, et autres
Publié: (2025)

Induced Numerical Instability: Hidden Costs in Multimodal Large Language Models
par: Wong, Wai Tuck, et autres
Publié: (2026)

Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression
par: Zhou, Longsheng, et autres
Publié: (2026)

Concise Thoughts: Impact of Output Length on LLM Reasoning and Cost
par: Nayab, Sania, et autres
Publié: (2024)

K-SENSE: A Knowledge-Guided Self-Augmented Encoder for Neuro-Semantic Evaluation of Mental Health Conditions on Social Media
par: Yadav, Vijay
Publié: (2026)

LogQuant: Log-Distributed 2-Bit Quantization of KV Cache with Superior Accuracy Preservation
par: Chen, Han, et autres
Publié: (2025)

Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models
par: Liu, Ruikang, et autres
Publié: (2025)

The Impact of Quantization on Retrieval-Augmented Generation: An Analysis of Small LLMs
par: Yazan, Mert, et autres
Publié: (2024)

Quantization Meets Reasoning: Exploring LLM Low-Bit Quantization Degradation for Mathematical Reasoning
par: Li, Zhen, et autres
Publié: (2025)

FRACTURED-SORRY-Bench: Framework for Revealing Attacks in Conversational Turns Undermining Refusal Efficacy and Defenses over SORRY-Bench (Automated Multi-shot Jailbreaks)
par: Priyanshu, Aman, et autres
Publié: (2024)

Distilling the Essence: Efficient Reasoning Distillation via Sequence Truncation
par: Chen, Wei-Rui, et autres
Publié: (2025)

Overestimation in LLM Evaluation: A Controlled Large-Scale Study on Data Contamination's Impact on Machine Translation
par: Kocyigit, Muhammed Yusuf, et autres
Publié: (2025)

Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency
par: Husom, Erik Johannes, et autres
Publié: (2025)

Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs
par: Lin, Haokun, et autres
Publié: (2025)

Oh! We Freeze: Improving Quantized Knowledge Distillation via Signal Propagation Analysis for Large Language Models
par: Bhardwaj, Kartikeya, et autres
Publié: (2024)

Can LLMs Understand the Impact of Trauma? Costs and Benefits of LLMs Coding the Interviews of Firearm Violence Survivors
par: Zhu, Jessica H., et autres
Publié: (2026)

The Hidden AI Race: Tracking Environmental Costs of Innovation
par: Agarwal, Shyam, et autres
Publié: (2025)

Align-to-Distill: Trainable Attention Alignment for Knowledge Distillation in Neural Machine Translation
par: Jin, Heegon, et autres
Publié: (2024)

Evaluating Quantized Large Language Models
par: Li, Shiyao, et autres
Publié: (2024)

Distill-C: Enhanced NL2SQL via Distilled Customization with LLMs
par: Hoang, Cong Duy Vu, et autres
Publié: (2025)

Translate-and-Revise: Boosting Large Language Models for Constrained Translation
par: Huang, Pengcheng, et autres
Publié: (2024)

Enhancing Aviation Communication Transcription: Fine-Tuning Distil-Whisper with LoRA
par: Mirzaei, Shokoufeh, et autres
Publié: (2025)

EasyDistill: A Comprehensive Toolkit for Effective Knowledge Distillation of Large Language Models
par: Wang, Chengyu, et autres
Publié: (2025)

Thinking with DistilQwen: A Tale of Four Distilled Reasoning and Reward Model Series
par: Cai, Wenrui, et autres
Publié: (2025)

EmoDistill: Offline Emotion Skill Distillation for Language Model Agents in Adversarial Negotiation
par: Long, Yunbo, et autres
Publié: (2026)

Transformer-Encoder Trees for Efficient Multilingual Machine Translation and Speech Translation
par: Guan, Yiwen, et autres
Publié: (2025)

Translation of Multifaceted Data without Re-Training of Machine Translation Systems
par: Moon, Hyeonseok, et autres
Publié: (2024)

Date Fragments: A Hidden Bottleneck of Tokenization for Temporal Reasoning
par: Bhatia, Gagan, et autres
Publié: (2025)