Cover Image

Boosting Protein Language Models with Negative Sample Mining

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Yaoyao, Zhao, Xinjian, Song, Xiaozhuang, Wang, Benyou, Yu, Tianshu
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Underappreciated Power of Vision Models for Graph Structural Understanding
by: Zhao, Xinjian, et al.
Published: (2025)

RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
by: Liu, Wanlong, et al.
Published: (2024)

Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination
by: Song, Jongyoon, et al.
Published: (2024)

Enhancing Graph Self-Supervised Learning with Graph Interplay
by: Zhao, Xinjian, et al.
Published: (2024)

Does higher interpretability imply better utility? A Pairwise Analysis on Sparse Autoencoders
by: Wang, Xu, et al.
Published: (2025)

Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
by: Jian, Xiangru, et al.
Published: (2024)

Evaluating Negative Sampling Approaches for Neural Topic Models
by: Adhya, Suman, et al.
Published: (2025)

Graph Learning with Distributional Edge Layouts
by: Zhao, Xinjian, et al.
Published: (2024)

Self-Generated Critiques Boost Reward Modeling for Language Models
by: Yu, Yue, et al.
Published: (2024)

Self-Evolving Critique Abilities in Large Language Models
by: Tang, Zhengyang, et al.
Published: (2025)

Instruction Mining: Instruction Data Selection for Tuning Large Language Models
by: Cao, Yihan, et al.
Published: (2023)

Boosting Large Language Models with Mask Fine-Tuning
by: Zhang, Mingyuan, et al.
Published: (2025)

RealCritic: Towards Effectiveness-Driven Evaluation of Language Model Critiques
by: Tang, Zhengyang, et al.
Published: (2025)

Mining Intrinsic Rewards from LLM Hidden States for Efficient Best-of-N Sampling
by: Guo, Jizhou, et al.
Published: (2025)

Systematic Outliers in Large Language Models
by: An, Yongqi, et al.
Published: (2025)

MPO: Boosting LLM Agents with Meta Plan Optimization
by: Xiong, Weimin, et al.
Published: (2025)

MathScale: Scaling Instruction Tuning for Mathematical Reasoning
by: Tang, Zhengyang, et al.
Published: (2024)

Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
by: Wang, Xu, et al.
Published: (2025)

BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning
by: Zhang, Beichen, et al.
Published: (2025)

FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling
by: Zhao, Weilin, et al.
Published: (2025)

Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning
by: Zhang, Ruiqi, et al.
Published: (2024)

MPPO: Multi Pair-wise Preference Optimization for LLMs with Arbitrary Negative Samples
by: Xie, Shuo, et al.
Published: (2024)

Knowledge Editing on Black-box Large Language Models
by: Song, Xiaoshuai, et al.
Published: (2024)

Enhancing Retrieval Performance: An Ensemble Approach For Hard Negative Mining
by: Meghwani, Hansa
Published: (2024)

Position Engineering: Boosting Large Language Models through Positional Information Manipulation
by: He, Zhiyuan, et al.
Published: (2024)

Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation
by: Nadeem, Mohammad, et al.
Published: (2024)

DIDS: Domain Impact-aware Data Sampling for Large Language Model Training
by: Shi, Weijie, et al.
Published: (2025)

Causal Evaluation of Language Models
by: Chen, Sirui, et al.
Published: (2024)

UltraFeedback: Boosting Language Models with Scaled AI Feedback
by: Cui, Ganqu, et al.
Published: (2023)

Instruction Following by Principled Boosting Attention of Large Language Models
by: Guardieiro, Vitoria, et al.
Published: (2025)

Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis
by: Jantre, Sanket, et al.
Published: (2025)

Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference
by: Hart, Anna, et al.
Published: (2026)

Modality-Balancing Preference Optimization of Large Multimodal Models by Adversarial Negative Mining
by: Liu, Chenxi, et al.
Published: (2025)

Sample-aware Adaptive Structured Pruning for Large Language Models
by: Kong, Jun, et al.
Published: (2025)

AdapThink: Adaptive Thinking Preferences for Reasoning Language Model
by: Wan, Xu, et al.
Published: (2025)

Sliding Window Attention Training for Efficient Large Language Models
by: Fu, Zichuan, et al.
Published: (2025)

Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
by: Chen, Sijia, et al.
Published: (2024)

Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers
by: Du, Yixuan, et al.
Published: (2026)

BioPars: A Pretrained Biomedical Large Language Model for Persian Biomedical Text Mining
by: Merzah, Baqer M., et al.
Published: (2025)

SLOT: Sample-specific Language Model Optimization at Test-time
by: Hu, Yang, et al.
Published: (2025)