-
Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing
Paper • 2404.12253 • Published • 55 -
FlowMind: Automatic Workflow Generation with LLMs
Paper • 2404.13050 • Published • 34 -
How Far Can We Go with Practical Function-Level Program Repair?
Paper • 2404.12833 • Published • 7 -
Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models
Paper • 2404.18796 • Published • 69
Collections
Discover the best community collections!
Collections including paper arxiv:2501.06252
-
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 126 -
Evolutionary Optimization of Model Merging Recipes
Paper • 2403.13187 • Published • 51 -
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Paper • 2402.03766 • Published • 14 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 65
-
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 24 -
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 60 -
Direct Preference Optimization Using Sparse Feature-Level Constraints
Paper • 2411.07618 • Published • 15 -
Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 53
-
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 6 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 21 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 12 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 67
-
PockEngine: Sparse and Efficient Fine-tuning in a Pocket
Paper • 2310.17752 • Published • 12 -
S-LoRA: Serving Thousands of Concurrent LoRA Adapters
Paper • 2311.03285 • Published • 30 -
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Paper • 2311.06243 • Published • 18 -
Fine-tuning Language Models for Factuality
Paper • 2311.08401 • Published • 29
-
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 44 -
PaLI-3 Vision Language Models: Smaller, Faster, Stronger
Paper • 2310.09199 • Published • 26 -
Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams
Paper • 2310.08678 • Published • 13 -
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
Paper • 2310.09478 • Published • 20