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Collections including paper arxiv:2406.17245

AI Paper of the Day

A collection of papers that I think are interesting, one added each day

Can Large Language Models Understand Context?

Paper • 2402.00858 • Published Feb 1 • 20
OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 75
Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 135
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity

Paper • 2401.17072 • Published Jan 30 • 23

Unlocking Continual Learning Abilities in Language Models

Paper • 2406.17245 • Published 8 days ago • 27
Can Few-shot Work in Long-Context? Recycling the Context to Generate Demonstrations

Paper • 2406.13632 • Published 13 days ago • 5
Read Anywhere Pointed: Layout-aware GUI Screen Reading with Tree-of-Lens Grounding

Paper • 2406.19263 • Published 5 days ago • 9
Can LLMs Learn by Teaching? A Preliminary Study

Paper • 2406.14629 • Published 12 days ago • 16

Unlocking Continual Learning Abilities in Language Models

Paper • 2406.17245 • Published 8 days ago • 27

Large Language Model Unlearning via Embedding-Corrupted Prompts

Paper • 2406.07933 • Published 21 days ago • 6
Block Transformer: Global-to-Local Language Modeling for Fast Inference

Paper • 2406.02657 • Published 28 days ago • 35
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning

Paper • 2406.12050 • Published 15 days ago • 10
How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Paper • 2406.11813 • Published 15 days ago • 28

Foundation AI Papers (II)

Iterative Reasoning Preference Optimization

Paper • 2404.19733 • Published Apr 30 • 44
Better & Faster Large Language Models via Multi-token Prediction

Paper • 2404.19737 • Published Apr 30 • 65
ORPO: Monolithic Preference Optimization without Reference Model

Paper • 2403.07691 • Published Mar 12 • 59
KAN: Kolmogorov-Arnold Networks

Paper • 2404.19756 • Published Apr 30 • 102

Data Efficient Approaches

How to Train Data-Efficient LLMs

Paper • 2402.09668 • Published Feb 15 • 34
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement

Paper • 2403.15042 • Published Mar 22 • 24
MAGID: An Automated Pipeline for Generating Synthetic Multi-modal Datasets

Paper • 2403.03194 • Published Mar 5 • 11
Orca-Math: Unlocking the potential of SLMs in Grade School Math

Paper • 2402.14830 • Published Feb 16 • 23

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30 • 15
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Paper • 2401.15688 • Published Jan 28 • 11
SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Paper • 2401.15024 • Published Jan 26 • 63
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities

Paper • 2401.15071 • Published Jan 26 • 33

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Paper • 2401.10774 • Published Jan 19 • 50
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Paper • 2401.06761 • Published Jan 12 • 1
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache

Paper • 2401.02669 • Published Jan 5 • 12
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 47

about 18 hours ago

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 135
Orion-14B: Open-source Multilingual Large Language Models

Paper • 2401.12246 • Published Jan 20 • 10
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 47
MM-LLMs: Recent Advances in MultiModal Large Language Models

Paper • 2401.13601 • Published Jan 24 • 41

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