Simeon Emanuilov PRO
s-emanuilov
AI & ML interests
Software Engineer, PhD | Building production ML/DL systems and AI tools
Recent Activity
liked
a model
6 days ago
google/translategemma-4b-it
liked
a dataset
8 days ago
HuggingFaceFW/finetranslations
liked
a model
8 days ago
zai-org/GLM-Image
Organizations
A collection of models along with the training dataset, designed to improve search queries and retrieval in RAG systems.
Papers on AI models that combine vision and language capabilities.
-
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Paper • 2501.06186 • Published • 65 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10
Papers exploring efficient and lightweight language models that achieve strong performance while being smaller and faster than large foundation models
Papers exploring vector representations of text and other data types, focusing on embedding models, techniques, and applications for semantic search.
A series of open-source Bulgarian language models fine-tuned for function calling and tool use. 2.6B, 9B, and 27B parameter variants.
Papers to improve reasoning capabilities of language models
Papers exploring autonomous AI systems and frameworks for building intelligent agents that can perceive environment, plan actions and use tools.
-
Agent Laboratory: Using LLM Agents as Research Assistants
Paper • 2501.04227 • Published • 95 -
Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains
Paper • 2501.05707 • Published • 20 -
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training
Paper • 2501.11425 • Published • 109
Papers exploring RAG techniques that combine language models with external knowledge retrieval to improve accuracy and reduce hallucinations.
A series of open-source Bulgarian language models fine-tuned for function calling and tool use. 2.6B, 9B, and 27B parameter variants.
A collection of models along with the training dataset, designed to improve search queries and retrieval in RAG systems.
Papers to improve reasoning capabilities of language models
Papers on AI models that combine vision and language capabilities.
-
LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token
Paper • 2501.03895 • Published • 52 -
LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Paper • 2501.06186 • Published • 65 -
Multimodal LLMs Can Reason about Aesthetics in Zero-Shot
Paper • 2501.09012 • Published • 10
Papers exploring autonomous AI systems and frameworks for building intelligent agents that can perceive environment, plan actions and use tools.
-
Agent Laboratory: Using LLM Agents as Research Assistants
Paper • 2501.04227 • Published • 95 -
Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains
Paper • 2501.05707 • Published • 20 -
Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training
Paper • 2501.11425 • Published • 109
Papers exploring efficient and lightweight language models that achieve strong performance while being smaller and faster than large foundation models
Papers exploring RAG techniques that combine language models with external knowledge retrieval to improve accuracy and reduce hallucinations.
Papers exploring vector representations of text and other data types, focusing on embedding models, techniques, and applications for semantic search.