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Collections including paper arxiv:2407.01284

about 19 hours ago

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6 • 24
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6 • 12
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 36
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

Papers I want to read

Papers in my to-read list

RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13 • 65
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 125
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 52
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 84

SpreadsheetLLM: Encoding Spreadsheets for Large Language Models

Paper • 2407.09025 • Published Jul 12 • 120
Human-like Episodic Memory for Infinite Context LLMs

Paper • 2407.09450 • Published Jul 12 • 56
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models

Paper • 2407.05131 • Published Jul 6 • 22
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?

Paper • 2407.01284 • Published Jul 1 • 75

Unlocking Continual Learning Abilities in Language Models

Paper • 2406.17245 • Published Jun 25 • 27
A Closer Look into Mixture-of-Experts in Large Language Models

Paper • 2406.18219 • Published Jun 26 • 15
Symbolic Learning Enables Self-Evolving Agents

Paper • 2406.18532 • Published Jun 26 • 10
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs

Paper • 2406.18629 • Published Jun 26 • 38

Papers - Image - Charts - QA - Reasoning

CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

Paper • 2406.18521 • Published Jun 26 • 25
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?

Paper • 2407.01284 • Published Jul 1 • 75
ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild

Paper • 2407.04172 • Published Jul 4 • 22

BLINK: Multimodal Large Language Models Can See but Not Perceive

Paper • 2404.12390 • Published Apr 18 • 24
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension

Paper • 2404.16790 • Published Apr 25 • 7
Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots

Paper • 2405.07990 • Published May 13 • 16
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding

Paper • 2406.09411 • Published Jun 13 • 18

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data

Paper • 2404.15653 • Published Apr 24 • 26
MoDE: CLIP Data Experts via Clustering

Paper • 2404.16030 • Published Apr 24 • 12
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20 • 45
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21 • 28

Papers - Math - Reasoning

Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2 • 43
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline

Paper • 2404.02893 • Published Apr 3 • 19
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Paper • 2309.12284 • Published Sep 21, 2023 • 18
Premise Order Matters in Reasoning with Large Language Models

Paper • 2402.08939 • Published Feb 14 • 24

Papers - Benchmarks - Math

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Paper • 2403.14624 • Published Mar 21 • 50
Challenge LLMs to Reason About Reasoning: A Benchmark to Unveil Cognitive Depth in LLMs

Paper • 2312.17080 • Published Dec 28, 2023 • 1
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?

Paper • 2407.01284 • Published Jul 1 • 75

Papers - Image - Math

MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Paper • 2403.14624 • Published Mar 21 • 50
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?

Paper • 2407.01284 • Published Jul 1 • 75
MAVIS: Mathematical Visual Instruction Tuning

Paper • 2407.08739 • Published Jul 11 • 30

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