Trending Research
From Words to Numbers: Your Large Language Model Is Secretly A Capable Regressor When Given In-Context Examples
We analyze how well pre-trained large language models (e. g., Llama2, GPT-4, Claude 3, etc) can do linear and non-linear regression when given in-context examples, without any additional training or gradient updates.
Vision-Language Pre-Training for Boosting Scene Text Detectors
AlibabaResearch/AdvancedLiterateMachinery
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CVPR 2022
In this paper, we specifically adapt vision-language joint learning for scene text detection, a task that intrinsically involves cross-modal interaction between the two modalities: vision and language, since text is the written form of language.
Levenshtein OCR
AlibabaResearch/AdvancedLiterateMachinery
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A novel scene text recognizer based on Vision-Language Transformer (VLT) is presented.
LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding
alibabaresearch/advancedliteratemachinery
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The core of LayoutLLM is a layout instruction tuning strategy, which is specially designed to enhance the comprehension and utilization of document layouts.
OmniFusion Technical Report
We propose an \textit{OmniFusion} model based on a pretrained LLM and adapters for visual modality.
Ranked #36 on
Visual Question Answering
on MM-Vet
ReFT: Representation Finetuning for Language Models
LoReFT is a drop-in replacement for existing PEFTs and learns interventions that are 10x-50x more parameter-efficient than prior state-of-the-art PEFTs.
Video-Based Human Pose Regression via Decoupled Space-Time Aggregation
zgspose/dsta
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In light of this, we propose a novel Decoupled Space-Time Aggregation network (DSTA) to separately capture the spatial contexts between adjacent joints and the temporal cues of each individual joint, thereby avoiding the conflation of spatiotemporal dimensions.
Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation
sail-sg/clot
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To this end, we study LLMs on the popular Oogiri game which needs participants to have good creativity and strong associative thinking for responding unexpectedly and humorously to the given image, text, or both, and thus is suitable for LoT study.
GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo
wuuu3511/gomvs
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More specifically, we correspond and propagate adjacent costs to the reference pixel by leveraging the local geometric smoothness in conjunction with surface normals.
Hash3D: Training-free Acceleration for 3D Generation
Adamdad/hash3D
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The evolution of 3D generative modeling has been notably propelled by the adoption of 2D diffusion models.
