Cover Image

Not Everything is All You Need: Toward Low-Redundant Optimization for Large Language Model Alignment

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Zhipeng, Zhou, Kun, Zhao, Wayne Xin, Wang, Jingyuan, Wen, Ji-Rong
Format:	Preprint
Published:	2024
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration
by: Chen, Zhipeng, et al.
Published: (2026)

Extracting and Combining Abilities For Building Multi-lingual Ability-enhanced Large Language Models
by: Chen, Zhipeng, et al.
Published: (2024)

Images are Achilles' Heel of Alignment: Exploiting Visual Vulnerabilities for Jailbreaking Multimodal Large Language Models
by: Li, Yifan, et al.
Published: (2024)

Do we Really Need Visual Instructions? Towards Visual Instruction-Free Fine-tuning for Large Vision-Language Models
by: Liu, Zikang, et al.
Published: (2025)

Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models
by: Wang, Xiaolei, et al.
Published: (2023)

Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint
by: Chen, Zhipeng, et al.
Published: (2024)

Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models
by: Sun, Haoxiang, et al.
Published: (2025)

Unleashing the Potential of Large Language Models as Prompt Optimizers: Analogical Analysis with Gradient-based Model Optimizers
by: Tang, Xinyu, et al.
Published: (2024)

Adaptive Ability Decomposing for Unlocking Large Reasoning Model Effective Reinforcement Learning
by: Chen, Zhipeng, et al.
Published: (2026)

Grimoire is All You Need for Enhancing Large Language Models
by: Chen, Ding, et al.
Published: (2024)

ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting
by: Cheng, Xiaoxue, et al.
Published: (2024)

Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models
by: Tyukin, Georgy, et al.
Published: (2024)

Self-Calibrated Listwise Reranking with Large Language Models
by: Ren, Ruiyang, et al.
Published: (2024)

ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph
by: Jiang, Jinhao, et al.
Published: (2023)

Towards Coarse-to-Fine Evaluation of Inference Efficiency for Large Language Models
by: Chen, Yushuo, et al.
Published: (2024)

Unveiling the Flaws: Exploring Imperfections in Synthetic Data and Mitigation Strategies for Large Language Models
by: Chen, Jie, et al.
Published: (2024)

BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models
by: Dong, Zican, et al.
Published: (2023)

ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
by: Men, Xin, et al.
Published: (2024)

Neuron-based Personality Trait Induction in Large Language Models
by: Deng, Jia, et al.
Published: (2024)

Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment
by: Guo, Geyang, et al.
Published: (2023)

Decomposing the Entropy-Performance Exchange: The Missing Keys to Unlocking Effective Reinforcement Learning
by: Deng, Jia, et al.
Published: (2025)

JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models
by: Zhou, Kun, et al.
Published: (2024)

Towards Effective and Efficient Continual Pre-training of Large Language Models
by: Chen, Jie, et al.
Published: (2024)

Exploring Context Window of Large Language Models via Decomposed Positional Vectors
by: Dong, Zican, et al.
Published: (2024)

Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models
by: Liu, Chaoqun, et al.
Published: (2024)

Parametric Knowledge is Not All You Need: Toward Honest Large Language Models via Retrieval of Pretraining Data
by: Kusuma, Christopher Adrian, et al.
Published: (2026)

The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models
by: Li, Junyi, et al.
Published: (2024)

ICPC-Eval: Probing the Frontiers of LLM Reasoning with Competitive Programming Contests
by: Xu, Shiyi, et al.
Published: (2025)

Addition is All You Need for Energy-efficient Language Models
by: Luo, Hongyin, et al.
Published: (2024)

Not All Tokens Are What You Need In Thinking
by: Yuan, Hang, et al.
Published: (2025)

BASES: Large-scale Web Search User Simulation with Large Language Model based Agents
by: Ren, Ruiyang, et al.
Published: (2024)

Analyzing and Mitigating Object Hallucination: A Training Bias Perspective
by: Li, Yifan, et al.
Published: (2025)

Guidance is All You Need: Temperature-Guided Reasoning in Large Language Models
by: Gomaa, Eyad, et al.
Published: (2024)

Not All Preferences are What You Need for Post-Training: Selective Alignment Strategy for Preference Optimization
by: Dong, Zhijin
Published: (2025)

Towards Effective Code-Integrated Reasoning
by: Bai, Fei, et al.
Published: (2025)

YuLan-Mini: An Open Data-efficient Language Model
by: Hu, Yiwen, et al.
Published: (2024)

Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment
by: Jiang, Jinhao, et al.
Published: (2024)

Small Agent Can Also Rock! Empowering Small Language Models as Hallucination Detector
by: Cheng, Xiaoxue, et al.
Published: (2024)

Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation
by: Ren, Ruiyang, et al.
Published: (2023)

DAWN-ICL: Strategic Planning of Problem-solving Trajectories for Zero-Shot In-Context Learning
by: Tang, Xinyu, et al.
Published: (2024)