Cover Image

Can a Crow Hatch a Falcon? Lineage Matters in Predicting Large Language Model Performance

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tamura, Takuya, Yano, Taro, Enomoto, Masafumi, Oyamada, Masafumi
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Can Large Language Models Invent Algorithms to Improve Themselves?: Algorithm Discovery for Recursive Self-Improvement through Reinforcement Learning
by: Ishibashi, Yoichi, et al.
Published: (2024)

An Empirical Study of LLM-as-a-Judge: How Design Choices Impact Evaluation Reliability
by: Yamauchi, Yusuke, et al.
Published: (2025)

LaMDAgent: An Autonomous Framework for Post-Training Pipeline Optimization via LLM Agents
by: Yano, Taro, et al.
Published: (2025)

Mining Hidden Thoughts from Texts: Evaluating Continual Pretraining with Synthetic Data for LLM Reasoning
by: Ishibashi, Yoichi, et al.
Published: (2025)

Revisiting Observation Reduction for Web Agents: Comprehensive Evaluation with a Lightweight Framework
by: Enomoto, Masafumi, et al.
Published: (2026)

Effective Harness Engineering for Algorithm Discovery with Coding Agents
by: Ishibashi, Yoichi, et al.
Published: (2026)

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

LightPAL: Lightweight Passage Retrieval for Open Domain Multi-Document Summarization
by: Enomoto, Masafumi, et al.
Published: (2024)

Context Quality Matters in Training Fusion-in-Decoder for Extractive Open-Domain Question Answering
by: Akimoto, Kosuke, et al.
Published: (2024)

$M^3$ Scaling Law: Optimizing Multi-Epoch, Multi-Lingual, and Multi-Stage Training for Low-Resource Language Models
by: Akimoto, Kosuke, et al.
Published: (2024)

Jellyfish: A Large Language Model for Data Preprocessing
by: Zhang, Haochen, et al.
Published: (2023)

cotomi Act: Learning to Automate Work by Watching You
by: Oyamada, Masafumi, et al.
Published: (2026)

Large Language Models as Data Preprocessors
by: Zhang, Haochen, et al.
Published: (2023)

Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domain
by: Ozaki, Shintaro, et al.
Published: (2024)

On Synthesizing Data for Context Attribution in Question Answering
by: Radevski, Gorjan, et al.
Published: (2025)

Best-of-$\infty$ -- Asymptotic Performance of Test-Time LLM Ensembling
by: Komiyama, Junpei, et al.
Published: (2025)

Can We Predict Performance of Large Models across Vision-Language Tasks?
by: Zhao, Qinyu, et al.
Published: (2024)

Direct Quantized Training of Language Models with Stochastic Rounding
by: Zhao, Kaiyan, et al.
Published: (2024)

Dutch CrowS-Pairs: Adapting a Challenge Dataset for Measuring Social Biases in Language Models for Dutch
by: Strazda, Elza, et al.
Published: (2025)

STEP: Staged Parameter-Efficient Pre-training for Large Language Models
by: Yano, Kazuki, et al.
Published: (2025)

Constructive Approach to Bidirectional Influence between Qualia Structure and Language Emergence
by: Taniguchi, Tadahiro, et al.
Published: (2024)

Can Large Language Models Predict Antimicrobial Resistance Gene?
by: Yoo, Hyunwoo
Published: (2025)

Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance
by: Zuo, Jingwei, et al.
Published: (2025)

Can Large Language Models Robustly Perform Natural Language Inference for Japanese Comparatives?
by: Mikami, Yosuke, et al.
Published: (2025)

From Chat to Checkup: Can Large Language Models Assist in Diabetes Prediction?
by: Sakib, Shadman, et al.
Published: (2025)

Can Large Language Models Predict the Outcome of Judicial Decisions?
by: Kmainasi, Mohamed Bayan, et al.
Published: (2025)

Regio‐ and Enantioselective Synthesis of Succinimides Bearing All‐Carbon Quaternary Centers Using a Chiral Phenanthroline‐Palladium Catalyst
by: Yudai Kuroiwa, et al.
Published: (2024)

Large Vocabulary Size Improves Large Language Models
by: Takase, Sho, et al.
Published: (2024)

Can Large Language Models Predict Associations Among Human Attitudes?
by: Ma, Ana, et al.
Published: (2025)

Can Large Language Models Understand Context?
by: Zhu, Yilun, et al.
Published: (2024)

Can Large Language Models Identify Authorship?
by: Huang, Baixiang, et al.
Published: (2024)

PoC: Performance-oriented Context Compression for Large Language Models via Performance Prediction
by: Zhao, Runsong, et al.
Published: (2026)

Can Large Language Models abstract Medical Coded Language?
by: Lee, Simon A., et al.
Published: (2024)

Collaborative Performance Prediction for Large Language Models
by: Zhang, Qiyuan, et al.
Published: (2024)

Can Language Models Induce Grammatical Knowledge from Indirect Evidence?
by: Oba, Miyu, et al.
Published: (2024)

Performance of Recent Large Language Models for a Low-Resourced Language
by: Jayakody, Ravindu, et al.
Published: (2024)

Can Large Language Models Make Everyone Happy?
by: Naseem, Usman, et al.
Published: (2026)

Can Multimodal Large Language Model Think Analogically?
by: Guo, Diandian, et al.
Published: (2024)

Large Language Models Can Learn Temporal Reasoning
by: Xiong, Siheng, et al.
Published: (2024)

Cuckoo: An IE Free Rider Hatched by Massive Nutrition in LLM's Nest
by: Peng, Letian, et al.
Published: (2025)