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Collections including paper arxiv:2407.01284

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

Paper • 2402.04252 • Published Feb 6 • 25
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 • 39
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 20

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 • 46
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention

Paper • 2405.12981 • Published May 21 • 28

MADLAD-400: A Multilingual And Document-Level Large Audited Dataset

Paper • 2309.04662 • Published Sep 9, 2023 • 22
Neurons in Large Language Models: Dead, N-gram, Positional

Paper • 2309.04827 • Published Sep 9, 2023 • 16
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

Paper • 2309.05516 • Published Sep 11, 2023 • 9
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs

Paper • 2309.03907 • Published May 18, 2023 • 10

SpreadsheetLLM: Encoding Spreadsheets for Large Language Models

Paper • 2407.09025 • Published Jul 12 • 129
Human-like Episodic Memory for Infinite Context LLMs

Paper • 2407.09450 • Published Jul 12 • 59
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models

Paper • 2407.05131 • Published Jul 6 • 24
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 • 28
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 • 11
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs

Paper • 2406.18629 • Published Jun 26 • 41

Papers - Image - Charts - QA - Reasoning

CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs

Paper • 2406.18521 • Published Jun 26 • 28
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

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 • 66
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 126
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 86

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

Papers - Math - Reasoning

Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2 • 44
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline

Paper • 2404.02893 • Published Apr 3 • 20
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 • 27

Papers - Benchmarks - Math

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

Paper • 2403.14624 • Published Mar 21 • 51
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
DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models

Paper • 2411.00836 • Published Oct 29 • 15

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