LoRA+: Efficient Low Rank Adaptation of Large Models
Paper
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2402.12354
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Published
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5
Papers
Large Language Model (LLM) and NLP related papers.
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The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 13 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 10 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 62 -
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
Paper • 2311.07463 • Published • 13 -
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
Paper • 2305.07185 • Published • 8 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43 -
PEFTDebias : Capturing debiasing information using PEFTs
Paper • 2312.00434 • Published • 1 -
From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformers
Paper • 2402.01911 • Published • 2 -
Empirical Study of PEFT techniques for Winter Wheat Segmentation
Paper • 2310.01825 • Published • 2 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 24 -
L4Q: Parameter Efficient Quantization-Aware Training on Large Language Models via LoRA-wise LSQ
Paper • 2402.04902 • Published • 1 -
Self-Instruct: Aligning Language Model with Self Generated Instructions
Paper • 2212.10560 • Published • 5 -
Efficient Training of Language Models to Fill in the Middle
Paper • 2207.14255 • Published • 1 -
Genie: Generative Interactive Environments
Paper • 2402.15391 • Published • 67 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 23 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 560 -
DiffuseKronA: A Parameter Efficient Fine-tuning Method for Personalized Diffusion Model
Paper • 2402.17412 • Published • 21 -
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT
Paper • 2402.16840 • Published • 23 -
LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
Paper • 2402.10524 • Published • 19 -
FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models
Paper • 2402.10986 • Published • 73 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 120 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 44 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 16 -
Design2Code: How Far Are We From Automating Front-End Engineering?
Paper • 2403.03163 • Published • 92 -
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs
Paper • 2403.02775 • Published • 11 -
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
Paper • 2402.10176 • Published • 32 -
OneBit: Towards Extremely Low-bit Large Language Models
Paper • 2402.11295 • Published • 21 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 57 -
Stealing Part of a Production Language Model
Paper • 2403.06634 • Published • 85 -
Adding NVMe SSDs to Enable and Accelerate 100B Model Fine-tuning on a Single GPU
Paper • 2403.06504 • Published • 52 -
An Image is Worth 1/2 Tokens After Layer 2: Plug-and-Play Inference Acceleration for Large Vision-Language Models
Paper • 2403.06764 • Published • 24 -
V3D: Video Diffusion Models are Effective 3D Generators
Paper • 2403.06738 • Published • 27 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 49 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 69 -
GiT: Towards Generalist Vision Transformer through Universal Language Interface
Paper • 2403.09394 • Published • 24 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 119 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 54 -
ORPO: Monolithic Preference Optimization without Reference Model
Paper • 2403.07691 • Published • 53 -
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Paper • 2403.13372 • Published • 50 -
Evolutionary Optimization of Model Merging Recipes
Paper • 2403.13187 • Published • 44 -
Matryoshka: Stealing Functionality of Private ML Data by Hiding Models in Model
Paper • 2206.14371 • Published • 3 -
sDPO: Don't Use Your Data All at Once
Paper • 2403.19270 • Published • 30 -
Model Stock: All we need is just a few fine-tuned models
Paper • 2403.19522 • Published • 9 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 98 -
Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 31 -
Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding
Paper • 2403.04797 • Published • 1 -
ReFT: Representation Finetuning for Language Models
Paper • 2404.03592 • Published • 66 -
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Paper • 2403.07816 • Published • 37 -
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Paper • 2402.01739 • Published • 26 -
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order
Paper • 2404.00399 • Published • 39 -
Latxa: An Open Language Model and Evaluation Suite for Basque
Paper • 2403.20266 • Published • 3 -
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
Paper • 2404.05961 • Published • 61 -
More Agents Is All You Need
Paper • 2402.05120 • Published • 46 -
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
Paper • 2404.00456 • Published • 3 -
Learn Your Reference Model for Real Good Alignment
Paper • 2404.09656 • Published • 79 -
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)
Paper • 2404.00579 • Published • 1 -
RoFormer: Enhanced Transformer with Rotary Position Embedding
Paper • 2104.09864 • Published • 7 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 57 -
Parameter Efficient Fine Tuning: A Comprehensive Analysis Across Applications
Paper • 2404.13506 • Published • 1