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Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs
Paper • 2407.00653 • Published • 11 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 41 -
Whiteboard-of-Thought: Thinking Step-by-Step Across Modalities
Paper • 2406.14562 • Published • 28 -
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
Paper • 2406.04271 • Published • 29
Collections
Discover the best community collections!
Collections including paper arxiv:2406.09308
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Instruction Pre-Training: Language Models are Supervised Multitask Learners
Paper • 2406.14491 • Published • 87 -
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Paper • 2405.21060 • Published • 64 -
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Paper • 2405.20541 • Published • 22 -
MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark
Paper • 2406.01574 • Published • 44
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mDPO: Conditional Preference Optimization for Multimodal Large Language Models
Paper • 2406.11839 • Published • 37 -
Pandora: Towards General World Model with Natural Language Actions and Video States
Paper • 2406.09455 • Published • 15 -
WPO: Enhancing RLHF with Weighted Preference Optimization
Paper • 2406.11827 • Published • 14 -
In-Context Editing: Learning Knowledge from Self-Induced Distributions
Paper • 2406.11194 • Published • 15
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Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
Paper • 2406.09403 • Published • 19 -
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Paper • 2406.09411 • Published • 18 -
Transformers meet Neural Algorithmic Reasoners
Paper • 2406.09308 • Published • 43
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Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models
Paper • 2402.14848 • Published • 18 -
The Prompt Report: A Systematic Survey of Prompting Techniques
Paper • 2406.06608 • Published • 58 -
CRAG -- Comprehensive RAG Benchmark
Paper • 2406.04744 • Published • 44 -
Transformers meet Neural Algorithmic Reasoners
Paper • 2406.09308 • Published • 43
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MotionLLM: Understanding Human Behaviors from Human Motions and Videos
Paper • 2405.20340 • Published • 20 -
Spectrally Pruned Gaussian Fields with Neural Compensation
Paper • 2405.00676 • Published • 8 -
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
Paper • 2404.18212 • Published • 27 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 119
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FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 25 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 37 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 52 -
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture
Paper • 2405.18991 • Published • 12
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Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 64 -
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Paper • 2404.07839 • Published • 43 -
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Paper • 2404.05892 • Published • 33 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 125 -
Evolutionary Optimization of Model Merging Recipes
Paper • 2403.13187 • Published • 50 -
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Paper • 2402.03766 • Published • 13 -
LLM Agent Operating System
Paper • 2403.16971 • Published • 65
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Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 47 -
Linear Transformers are Versatile In-Context Learners
Paper • 2402.14180 • Published • 6 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 19 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 605