Guardado en:
| Autores principales: | Tang, Shengkun, Ma, Liqun, Li, Haonan, Sun, Mingjie, Shen, Zhiqiang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2411.11843 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive Distillation
por: Ma, Liqun, et al.
Publicado: (2024)
por: Ma, Liqun, et al.
Publicado: (2024)
Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models
por: Das, Rocktim Jyoti, et al.
Publicado: (2023)
por: Das, Rocktim Jyoti, et al.
Publicado: (2023)
Sink-Aware Pruning for Diffusion Language Models
por: Myrzakhan, Aidar, et al.
Publicado: (2026)
por: Myrzakhan, Aidar, et al.
Publicado: (2026)
DocMamba: Efficient Document Pre-training with State Space Model
por: Hu, Pengfei, et al.
Publicado: (2024)
por: Hu, Pengfei, et al.
Publicado: (2024)
MemMamba: Rethinking Memory Patterns in State Space Model
por: Wang, Youjin, et al.
Publicado: (2025)
por: Wang, Youjin, et al.
Publicado: (2025)
Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark
por: Bsharat, Sondos Mahmoud, et al.
Publicado: (2025)
por: Bsharat, Sondos Mahmoud, et al.
Publicado: (2025)
Making Pre-trained Language Models Better Continual Few-Shot Relation Extractors
por: Ma, Shengkun, et al.
Publicado: (2024)
por: Ma, Shengkun, et al.
Publicado: (2024)
MRCEval: A Comprehensive, Challenging and Accessible Machine Reading Comprehension Benchmark
por: Ma, Shengkun, et al.
Publicado: (2025)
por: Ma, Shengkun, et al.
Publicado: (2025)
SlimQwen: Exploring the Pruning and Distillation in Large MoE Model Pre-training
por: Tang, Shengkun, et al.
Publicado: (2026)
por: Tang, Shengkun, et al.
Publicado: (2026)
The Computational Limits of State-Space Models and Mamba via the Lens of Circuit Complexity
por: Chen, Yifang, et al.
Publicado: (2024)
por: Chen, Yifang, et al.
Publicado: (2024)
SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
por: Cheng, Wenhua, et al.
Publicado: (2025)
por: Cheng, Wenhua, et al.
Publicado: (2025)
Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity
por: Liang, Weixin, et al.
Publicado: (2025)
por: Liang, Weixin, et al.
Publicado: (2025)
BlackMamba: Mixture of Experts for State-Space Models
por: Anthony, Quentin, et al.
Publicado: (2024)
por: Anthony, Quentin, et al.
Publicado: (2024)
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
por: Pióro, Maciej, et al.
Publicado: (2024)
por: Pióro, Maciej, et al.
Publicado: (2024)
Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models
por: NVIDIA, et al.
Publicado: (2025)
por: NVIDIA, et al.
Publicado: (2025)
RotateKV: Accurate and Robust 2-Bit KV Cache Quantization for LLMs via Outlier-Aware Adaptive Rotations
por: Su, Zunhai, et al.
Publicado: (2025)
por: Su, Zunhai, et al.
Publicado: (2025)
R2Gen-Mamba: A Selective State Space Model for Radiology Report Generation
por: Sun, Yongheng, et al.
Publicado: (2024)
por: Sun, Yongheng, et al.
Publicado: (2024)
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
por: NVIDIA, et al.
Publicado: (2025)
por: NVIDIA, et al.
Publicado: (2025)
SlimPajama-DC: Understanding Data Combinations for LLM Training
por: Shen, Zhiqiang, et al.
Publicado: (2023)
por: Shen, Zhiqiang, et al.
Publicado: (2023)
ECMNet:Lightweight Semantic Segmentation with Efficient CNN-Mamba Network
por: Du, Feixiang, et al.
Publicado: (2025)
por: Du, Feixiang, et al.
Publicado: (2025)
Revealing and Mitigating the Local Pattern Shortcuts of Mamba
por: You, Wangjie, et al.
Publicado: (2024)
por: You, Wangjie, et al.
Publicado: (2024)
EMBRE: Entity-aware Masking for Biomedical Relation Extraction
por: Li, Mingjie, et al.
Publicado: (2024)
por: Li, Mingjie, et al.
Publicado: (2024)
Stuffed Mamba: Oversized States Lead to the Inability to Forget
por: Chen, Yingfa, et al.
Publicado: (2024)
por: Chen, Yingfa, et al.
Publicado: (2024)
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
por: Li, Dengchun, et al.
Publicado: (2024)
por: Li, Dengchun, et al.
Publicado: (2024)
MoBiQuant: Mixture-of-Bits Quantization for Token-Adaptive Any-Precision LLM
por: Wang, Dongwei, et al.
Publicado: (2026)
por: Wang, Dongwei, et al.
Publicado: (2026)
Automated Classification of Tutors' Dialogue Acts Using Generative AI: A Case Study Using the CIMA Corpus
por: He, Liqun, et al.
Publicado: (2025)
por: He, Liqun, et al.
Publicado: (2025)
R2Q: Towards Robust 2-Bit Large Language Models via Residual Refinement Quantization
por: Chen, Jiayi, et al.
Publicado: (2025)
por: Chen, Jiayi, et al.
Publicado: (2025)
Mamba-Shedder: Post-Transformer Compression for Efficient Selective Structured State Space Models
por: Muñoz, J. Pablo, et al.
Publicado: (2025)
por: Muñoz, J. Pablo, et al.
Publicado: (2025)
Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4
por: Bsharat, Sondos Mahmoud, et al.
Publicado: (2023)
por: Bsharat, Sondos Mahmoud, et al.
Publicado: (2023)
ML-Mamba: Efficient Multi-Modal Large Language Model Utilizing Mamba-2
por: Huang, Wenjun, et al.
Publicado: (2024)
por: Huang, Wenjun, et al.
Publicado: (2024)
A Survey on Diffusion Language Models
por: Li, Tianyi, et al.
Publicado: (2025)
por: Li, Tianyi, et al.
Publicado: (2025)
TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding
por: Wu, Bingheng, et al.
Publicado: (2025)
por: Wu, Bingheng, et al.
Publicado: (2025)
Hidden State Poisoning Attacks against Mamba-based Language Models
por: Mercier, Alexandre Le, et al.
Publicado: (2026)
por: Mercier, Alexandre Le, et al.
Publicado: (2026)
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
por: Gao, Chengqian, et al.
Publicado: (2025)
por: Gao, Chengqian, et al.
Publicado: (2025)
BiLD: Bi-directional Logits Difference Loss for Large Language Model Distillation
por: Li, Minchong, et al.
Publicado: (2024)
por: Li, Minchong, et al.
Publicado: (2024)
Detoxification of Large Language Models through Output-layer Fusion with a Calibration Model
por: Tian, Yuanhe, et al.
Publicado: (2025)
por: Tian, Yuanhe, et al.
Publicado: (2025)
An Exploration of Mamba for Speech Self-Supervised Models
por: Lin, Tzu-Quan, et al.
Publicado: (2025)
por: Lin, Tzu-Quan, et al.
Publicado: (2025)
A Simple and Effective Pruning Approach for Large Language Models
por: Sun, Mingjie, et al.
Publicado: (2023)
por: Sun, Mingjie, et al.
Publicado: (2023)
Affective-NLI: Towards Accurate and Interpretable Personality Recognition in Conversation
por: Wen, Zhiyuan, et al.
Publicado: (2024)
por: Wen, Zhiyuan, et al.
Publicado: (2024)
ChatUIE: Exploring Chat-based Unified Information Extraction using Large Language Models
por: Xu, Jun, et al.
Publicado: (2024)
por: Xu, Jun, et al.
Publicado: (2024)
Ejemplares similares
-
FBI-LLM: Scaling Up Fully Binarized LLMs from Scratch via Autoregressive Distillation
por: Ma, Liqun, et al.
Publicado: (2024) -
Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models
por: Das, Rocktim Jyoti, et al.
Publicado: (2023) -
Sink-Aware Pruning for Diffusion Language Models
por: Myrzakhan, Aidar, et al.
Publicado: (2026) -
DocMamba: Efficient Document Pre-training with State Space Model
por: Hu, Pengfei, et al.
Publicado: (2024) -
MemMamba: Rethinking Memory Patterns in State Space Model
por: Wang, Youjin, et al.
Publicado: (2025)