Saved in:
| Main Authors: | Zou, Hongjian, Wang, Yidan, Ding, Qi, Liao, Yixuan, Chen, Xiaoxin |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.07363 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Caption First, VQA Second: Knowledge Density, Not Task Format, Drives Multimodal Scaling
by: Zou, Hongjian, et al.
Published: (2026)
by: Zou, Hongjian, et al.
Published: (2026)
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
by: Shum, Kashun, et al.
Published: (2025)
by: Shum, Kashun, et al.
Published: (2025)
Transformer-based Parameter Estimation in Statistics
by: Yin, Xiaoxin, et al.
Published: (2024)
by: Yin, Xiaoxin, et al.
Published: (2024)
ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Data
by: Wang, Chengsen, et al.
Published: (2025)
by: Wang, Chengsen, et al.
Published: (2025)
LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites
by: Jiang, Lei, et al.
Published: (2026)
by: Jiang, Lei, et al.
Published: (2026)
LLMCarbon: Modeling the end-to-end Carbon Footprint of Large Language Models
by: Faiz, Ahmad, et al.
Published: (2023)
by: Faiz, Ahmad, et al.
Published: (2023)
Block Circulant Adapter for Large Language Models
by: Ding, Xinyu, et al.
Published: (2025)
by: Ding, Xinyu, et al.
Published: (2025)
AlignBench: Benchmarking Chinese Alignment of Large Language Models
by: Liu, Xiao, et al.
Published: (2023)
by: Liu, Xiao, et al.
Published: (2023)
Parameter-Efficient Fine-Tuning with Circulant and Diagonal Vectors
by: Ding, Xinyu, et al.
Published: (2025)
by: Ding, Xinyu, et al.
Published: (2025)
Towards Understanding Valuable Preference Data for Large Language Model Alignment
by: Zhang, Zizhuo, et al.
Published: (2025)
by: Zhang, Zizhuo, et al.
Published: (2025)
From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
by: Chen, Hao, et al.
Published: (2026)
by: Chen, Hao, et al.
Published: (2026)
Shuttle Between the Instructions and the Parameters of Large Language Models
by: Sun, Wangtao, et al.
Published: (2025)
by: Sun, Wangtao, et al.
Published: (2025)
TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators
by: Li, Jianling, et al.
Published: (2025)
by: Li, Jianling, et al.
Published: (2025)
Towards Practical Benchmarking of Data Cleaning Techniques: On Generating Authentic Errors via Large Language Models
by: Liu, Xinyuan, et al.
Published: (2025)
by: Liu, Xinyuan, et al.
Published: (2025)
Ecosystem Graphs: The Social Footprint of Foundation Models
by: Bommasani, Rishi, et al.
Published: (2023)
by: Bommasani, Rishi, et al.
Published: (2023)
Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning
by: Liu, Guozhi, et al.
Published: (2025)
by: Liu, Guozhi, et al.
Published: (2025)
Efficient Alignment of Large Language Models via Data Sampling
by: Khera, Amrit, et al.
Published: (2024)
by: Khera, Amrit, et al.
Published: (2024)
On Large Language Model Continual Unlearning
by: Gao, Chongyang, et al.
Published: (2024)
by: Gao, Chongyang, et al.
Published: (2024)
How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence
by: Choi, Hyeong Kyu, et al.
Published: (2025)
by: Choi, Hyeong Kyu, et al.
Published: (2025)
Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models
by: Wang, Fei, et al.
Published: (2024)
by: Wang, Fei, et al.
Published: (2024)
Klein Model for Hyperbolic Neural Networks
by: Mao, Yidan, et al.
Published: (2024)
by: Mao, Yidan, et al.
Published: (2024)
Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
by: Wang, Chaoqi, et al.
Published: (2025)
by: Wang, Chaoqi, et al.
Published: (2025)
Conformal Tail Risk Control for Large Language Model Alignment
by: Chen, Catherine Yu-Chi, et al.
Published: (2025)
by: Chen, Catherine Yu-Chi, et al.
Published: (2025)
Discovering Implicit Large Language Model Alignment Objectives
by: Chen, Edward, et al.
Published: (2026)
by: Chen, Edward, et al.
Published: (2026)
Large Language Model Agent for Hyper-Parameter Optimization
by: Liu, Siyi, et al.
Published: (2024)
by: Liu, Siyi, et al.
Published: (2024)
Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models
by: Kaddour, Jean, et al.
Published: (2023)
by: Kaddour, Jean, et al.
Published: (2023)
CarbonScaling: Extending Neural Scaling Laws for Carbon Footprint in Large Language Models
by: Jiang, Lei, et al.
Published: (2025)
by: Jiang, Lei, et al.
Published: (2025)
Spatial Transfer Learning with Simple MLP
by: Yang, Hongjian
Published: (2024)
by: Yang, Hongjian
Published: (2024)
SAIL: Self-Improving Efficient Online Alignment of Large Language Models
by: Ding, Mucong, et al.
Published: (2024)
by: Ding, Mucong, et al.
Published: (2024)
Resource-Efficient Federated Fine-Tuning Large Language Models for Heterogeneous Data
by: Liu, Jun, et al.
Published: (2025)
by: Liu, Jun, et al.
Published: (2025)
Parameter-Efficient Tuning Large Language Models for Graph Representation Learning
by: Zhu, Qi, et al.
Published: (2024)
by: Zhu, Qi, et al.
Published: (2024)
Are Large Language Models Useful for Time Series Data Analysis?
by: Tang, Francis, et al.
Published: (2024)
by: Tang, Francis, et al.
Published: (2024)
Benchmarking Benchmark Leakage in Large Language Models
by: Xu, Ruijie, et al.
Published: (2024)
by: Xu, Ruijie, et al.
Published: (2024)
Kinematics-aware Trajectory Generation and Prediction with Latent Stochastic Differential Modeling
by: Jiao, Ruochen, et al.
Published: (2023)
by: Jiao, Ruochen, et al.
Published: (2023)
MergeQuant: Accurate 4-bit Static Quantization of Large Language Models by Channel-wise Calibration
by: Wang, Jinguang, et al.
Published: (2025)
by: Wang, Jinguang, et al.
Published: (2025)
SafeNeuron: Neuron-Level Safety Alignment for Large Language Models
by: Wang, Zhaoxin, et al.
Published: (2026)
by: Wang, Zhaoxin, et al.
Published: (2026)
MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models
by: Pandit, Shrey, et al.
Published: (2025)
by: Pandit, Shrey, et al.
Published: (2025)
ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models
by: Akhauri, Yash, et al.
Published: (2024)
by: Akhauri, Yash, et al.
Published: (2024)
Empowering Autonomous Driving with Large Language Models: A Safety Perspective
by: Wang, Yixuan, et al.
Published: (2023)
by: Wang, Yixuan, et al.
Published: (2023)
Automated Discovery of Integral with Deep Learning
by: Yin, Xiaoxin
Published: (2024)
by: Yin, Xiaoxin
Published: (2024)
Similar Items
-
Caption First, VQA Second: Knowledge Density, Not Task Format, Drives Multimodal Scaling
by: Zou, Hongjian, et al.
Published: (2026) -
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
by: Shum, Kashun, et al.
Published: (2025) -
Transformer-based Parameter Estimation in Statistics
by: Yin, Xiaoxin, et al.
Published: (2024) -
ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Data
by: Wang, Chengsen, et al.
Published: (2025) -
LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites
by: Jiang, Lei, et al.
Published: (2026)