Cover Image

More Human, More Efficient: Aligning Annotations with Quantized SLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wang, Jiayu, Lee, Junyoung
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

PopAlign: Diversifying Contrasting Patterns for a More Comprehensive Alignment
by: Wang, Zekun Moore, et al.
Published: (2024)

More Aligned, Less Diverse? Analyzing the Grammar and Lexicon of Two Generations of LLMs
by: Gude, Adrián, et al.
Published: (2026)

Dependency Parsing is More Parameter-Efficient with Normalization
by: Gajo, Paolo, et al.
Published: (2025)

Are Large Language Models More Empathetic than Humans?
by: Welivita, Anuradha, et al.
Published: (2024)

Who Relies More on World Knowledge and Bias for Syntactic Ambiguity Resolution: Humans or LLMs?
by: Lee, So Young, et al.
Published: (2025)

Towards Efficient Vision-Language Tuning: More Information Density, More Generalizability
by: Hao, Tianxiang, et al.
Published: (2023)

MoreHopQA: More Than Multi-hop Reasoning
by: Schnitzler, Julian, et al.
Published: (2024)

Is ChatGPT More Empathetic than Humans?
by: Welivita, Anuradha, et al.
Published: (2024)

Read More, Think More: Revisiting Observation Reduction for Web Agents
by: Enomoto, Masafumi, et al.
Published: (2026)

Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs
by: Li, Xiang, et al.
Published: (2025)

Acting Less is Reasoning More! Teaching Model to Act Efficiently
by: Wang, Hongru, et al.
Published: (2025)

Less is More for RAG: Information Gain Pruning for Generator-Aligned Reranking and Evidence Selection
by: Song, Zhipeng, et al.
Published: (2026)

Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling
by: Cook, Jack, et al.
Published: (2025)

KAIO: A Collection of More Challenging Korean Questions
by: Lee, Nahyun, et al.
Published: (2025)

Learning More from Less: Exploiting Counterfactuals for Data-Efficient Chart Understanding
by: Bao, Jianzhu, et al.
Published: (2026)

Large Language Models Portray Socially Subordinate Groups as More Homogeneous, Consistent with a Bias Observed in Humans
by: Lee, Messi H. J., et al.
Published: (2024)

Less is More: The Effectiveness of Compact Typological Language Representations
by: Ng, York Hay, et al.
Published: (2025)

More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering
by: Yao, Bingsheng, et al.
Published: (2023)

More is More: Addition Bias in Large Language Models
by: Santagata, Luca, et al.
Published: (2024)

Debating with More Persuasive LLMs Leads to More Truthful Answers
by: Khan, Akbir, et al.
Published: (2024)

More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
by: Li, Aaron J., et al.
Published: (2024)

Giving AI Personalities Leads to More Human-Like Reasoning
by: Nighojkar, Animesh, et al.
Published: (2025)

Less is More: Resource-Efficient Low-Rank Adaptation
by: Tian, Chunlin, et al.
Published: (2025)

More Than Bits: Multi-Envelope Double Binary Factorization for Extreme Quantization
by: Ichikawa, Yuma, et al.
Published: (2025)

More Thinking, More Bias: Length-Driven Position Bias in Reasoning Models
by: Wang, Xiao
Published: (2026)

From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered
by: Devic, Siddartha, et al.
Published: (2025)

Benchmarking LLMs and SLMs for patient reported outcomes
by: Marengo, Matteo, et al.
Published: (2024)

More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play
by: Wongkamjan, Wichayaporn, et al.
Published: (2024)

Less is More Tokens: Efficient Math Reasoning via Difficulty-Aware Chain-of-Thought Distillation
by: Waheed, Abdul, et al.
Published: (2025)

Less is More: Compact Clue Selection for Efficient Retrieval-Augmented Generation Reasoning
by: Zhang, Qianchi, et al.
Published: (2025)

More Rounds, More Noise: Why Multi-Turn Review Fails to Improve Cross-Context Verification
by: Tae-Eun, Song
Published: (2026)

Small Language Models can Outperform Humans in Short Creative Writing: A Study Comparing SLMs with Humans and LLMs
by: Marco, Guillermo, et al.
Published: (2024)

WKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More
by: Yue, Yuxuan, et al.
Published: (2024)

QAQ: Quality Adaptive Quantization for LLM KV Cache
by: Dong, Shichen, et al.
Published: (2024)

More Edits, More Stable: Understanding the Lifelong Normalization in Sequential Model Editing
by: Ma, Xin, et al.
Published: (2026)

Search More, Think Less: Rethinking Long-Horizon Agentic Search for Efficiency and Generalization
by: Chen, Qianben, et al.
Published: (2026)

G-Boost: Boosting Private SLMs with General LLMs
by: Fan, Yijiang, et al.
Published: (2025)

Return of the Encoder: Maximizing Parameter Efficiency for SLMs
by: Elfeki, Mohamed, et al.
Published: (2025)

Why Are Linear RNNs More Parallelizable?
by: Merrill, William, et al.
Published: (2026)

Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
by: Al-Tawaha, Ahmad, et al.
Published: (2026)