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Collections including paper arxiv:2403.15371

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

Paper • 2402.04252 • Published Feb 6 • 21
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6 • 9
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 31
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

Articles to be read.

Can large language models explore in-context?

Paper • 2403.15371 • Published Mar 22 • 30

Can large language models explore in-context?

Paper • 2403.15371 • Published Mar 22 • 30
Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2 • 41
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2 • 33
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences

Paper • 2404.03715 • Published Apr 4 • 58

Papers - University - Carnegie Mellon University

Can large language models explore in-context?

Paper • 2403.15371 • Published Mar 22 • 30
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2 • 33
PIQA: Reasoning about Physical Commonsense in Natural Language

Paper • 1911.11641 • Published Nov 26, 2019 • 2
AQuA: A Benchmarking Tool for Label Quality Assessment

Paper • 2306.09467 • Published Jun 15, 2023 • 1

Papers - Microsoft

about 5 hours ago

Can large language models explore in-context?

Paper • 2403.15371 • Published Mar 22 • 30
GaussianCube: Structuring Gaussian Splatting using Optimal Transport for 3D Generative Modeling

Paper • 2403.19655 • Published Mar 28 • 14
WavLLM: Towards Robust and Adaptive Speech Large Language Model

Paper • 2404.00656 • Published Mar 31 • 5
Enabling Memory Safety of C Programs using LLMs

Paper • 2404.01096 • Published Apr 1 • 1

Can large language models explore in-context?

Paper • 2403.15371 • Published Mar 22 • 30
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement

Paper • 2403.15042 • Published Mar 22 • 24
BLINK: Multimodal Large Language Models Can See but Not Perceive

Paper • 2404.12390 • Published Apr 18 • 23
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models

Paper • 2404.12387 • Published Apr 18 • 35

Papers - ICL - In-Context Learning

Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models

Paper • 2311.00871 • Published Nov 1, 2023 • 2
Can large language models explore in-context?

Paper • 2403.15371 • Published Mar 22 • 30
Data Distributional Properties Drive Emergent In-Context Learning in Transformers

Paper • 2205.05055 • Published Apr 22, 2022 • 2
Long-context LLMs Struggle with Long In-context Learning

Paper • 2404.02060 • Published Apr 2 • 33

Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset

Paper • 2403.09029 • Published Mar 14 • 52
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Paper • 2403.12968 • Published Mar 19 • 20
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 63
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Paper • 2403.09629 • Published Mar 14 • 54

Papers - Chain of Thought

Contrastive Decoding Improves Reasoning in Large Language Models

Paper • 2309.09117 • Published Sep 17, 2023 • 37
Chain-of-Thought Reasoning Without Prompting

Paper • 2402.10200 • Published Feb 15 • 91
MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Paper • 2403.14624 • Published Mar 21 • 50
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems

Paper • 2402.12875 • Published Feb 20 • 2

How Far Are We from Intelligent Visual Deductive Reasoning?

Paper • 2403.04732 • Published Mar 7 • 18
MoAI: Mixture of All Intelligence for Large Language and Vision Models

Paper • 2403.07508 • Published Mar 12 • 70
DragAnything: Motion Control for Anything using Entity Representation

Paper • 2403.07420 • Published Mar 12 • 11
Learning and Leveraging World Models in Visual Representation Learning

Paper • 2403.00504 • Published Mar 1 • 25

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