Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping
Paper
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2306.12981
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Published
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ly015
authored
12
papers
about 2 months ago
Towards Language-Driven Video Inpainting via Multimodal Large Language Models
Paper
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2401.10226
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Published
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1
OMG-Seg: Is One Model Good Enough For All Segmentation?
Paper
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2401.10229
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Published
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1
InternLM2 Technical Report
Paper
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2403.17297
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Published
•
33
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper
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2404.06512
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Published
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31
MG-LLaVA: Towards Multi-Granularity Visual Instruction Tuning
Paper
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2406.17770
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Published
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19
InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output
Paper
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2407.03320
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Published
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96
InternLM-Law: An Open Source Chinese Legal Large Language Model
Paper
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2406.14887
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Published
RTMW: Real-Time Multi-Person 2D and 3D Whole-body Pose Estimation
Paper
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2407.08634
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Published
An Open and Comprehensive Pipeline for Unified Object Grounding and Detection
Paper
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2401.02361
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Published
RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
Paper
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2303.07399
•
Published
MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space
Paper
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2504.13835
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Published
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38
Post
3508
🔥MedAgentBench Amazing Work🚀
Just explored #MedAgentBench from @Yale researchers and it's mind-blowing! They've created a cutting-edge benchmark that finally exposes the true capabilities of LLMs in complex medical reasoning.
⚡ Key discoveries:
DeepSeek R1 & OpenAI O3 dominate clinical reasoning tasks
Agent-based frameworks deliver exceptional performance-cost balance
Open-source alternatives are closing the gap at fraction of the cost
This work shatters previous benchmarks that failed to challenge today's advanced models.
The future of medical AI is here: https://github.com/gersteinlab/medagents-benchmark
#MedicalAI #MachineLearning #AIinHealthcare 🔥
Just explored #MedAgentBench from @Yale researchers and it's mind-blowing! They've created a cutting-edge benchmark that finally exposes the true capabilities of LLMs in complex medical reasoning.
⚡ Key discoveries:
DeepSeek R1 & OpenAI O3 dominate clinical reasoning tasks
Agent-based frameworks deliver exceptional performance-cost balance
Open-source alternatives are closing the gap at fraction of the cost
This work shatters previous benchmarks that failed to challenge today's advanced models.
The future of medical AI is here: https://github.com/gersteinlab/medagents-benchmark
#MedicalAI #MachineLearning #AIinHealthcare 🔥
vansin
authored
a
paper
9 months ago
Post
2225
With the open-weight release of CogVideoX-5B from THUDM, i.e. GLM team, the Video Generation Model (how about calling it VGM) field has officially became the next booming "LLM"
What does the landscape look like? What are other video generation models? This collection below is all your need.
xianbao/video-generation-models-66c350163c74f60f5c412af6
The above video is generated by @a-r-r-o-w with CogVideoX-5B, taken from a nice lookout for the field!
What does the landscape look like? What are other video generation models? This collection below is all your need.
xianbao/video-generation-models-66c350163c74f60f5c412af6
The above video is generated by @a-r-r-o-w with CogVideoX-5B, taken from a nice lookout for the field!
ly015
authored
a
paper
11 months ago
xianbao
authored
a
paper
12 months ago
Post
2001
Why Apache 2.0 Matters for LLMs 🤔
@01AI_Yi recently switched from a permissive & commercially friendly license, to Apache 2.0. And the community loved it! 🚀
@JustinLin610 also had a poll on model license and the majority votes for Apache 2.0.
Why it is a Big Deal? ⬇️
📚 Legal Simplicity: Custom licenses need costly & time-consuming legal review. Apache 2.0 is well-known & easier for legal teams to handle.
👩💻 Developer-Friendly: Legal docs are a pain for devs! Apache 2.0 is well-known and tech-friendly, making it easier for non-native developers to understand the implications too.
🔗 Easier Integration: Apache 2.0 is compatible with many other licenses, simplifying tasks like model merging with models of different licensing requirements.
🚫 No Permission Needed: Custom licenses often require explicit permission and additional documentation work of filling forms, creating barriers. Apache 2.0 removes this hurdle, letting devs focus on innovation.
There are a lot interesting discussions from
@JustinLin610 's poll: https://x.com/JustinLin610/status/1793559737482764375 which inspired this thread.
Any other thoughts? Let me know ^^
@01AI_Yi recently switched from a permissive & commercially friendly license, to Apache 2.0. And the community loved it! 🚀
@JustinLin610 also had a poll on model license and the majority votes for Apache 2.0.
Why it is a Big Deal? ⬇️
📚 Legal Simplicity: Custom licenses need costly & time-consuming legal review. Apache 2.0 is well-known & easier for legal teams to handle.
👩💻 Developer-Friendly: Legal docs are a pain for devs! Apache 2.0 is well-known and tech-friendly, making it easier for non-native developers to understand the implications too.
🔗 Easier Integration: Apache 2.0 is compatible with many other licenses, simplifying tasks like model merging with models of different licensing requirements.
🚫 No Permission Needed: Custom licenses often require explicit permission and additional documentation work of filling forms, creating barriers. Apache 2.0 removes this hurdle, letting devs focus on innovation.
There are a lot interesting discussions from
@JustinLin610 's poll: https://x.com/JustinLin610/status/1793559737482764375 which inspired this thread.
Any other thoughts? Let me know ^^
- 1 reply