Stars
[Arxiv] Official Responsibility for "SQL-R1: Training Natural Language to SQL Reasoning Model By Reinforcement Learning"
Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning, achieving state-of-the-art performance on 38 out of 60 public benchmarks.
Seed-Coder is a family of lightweight open-source code LLMs comprising base, instruct and reasoning models, developed by ByteDance Seed.
A library for prompt engineering and optimization (SAMMO = Structure-aware Multi-Objective Metaprompt Optimization)
The development and future prospects of multimodal reasoning models.
ArcticTraining is a framework designed to simplify and accelerate the post-training process for large language models (LLMs)
A Text-to-SQL Agent with Self-Refinement, Format Restriction, and Column Exploration
A framework for prompt tuning using Intent-based Prompt Calibration
A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning
Ming - facilitating advanced multimodal understanding and generation capabilities built upon the Ling LLM.
Agentic RAG R1 Framework via Reinforcement Learning
A list of VLMs tailored for medical RG and VQA; and a list of medical vision-language datasets
Vision Document Retrieval (ViDoRe): Benchmark. Evaluation code for the ColPali paper.
Filipino multi-modal NLP dataset. Consists of 350k+ Filipino news articles and associated images
Implementation and evaluation of multimodal RAG with text and image inputs for industrial applications
a state-of-the-art-level open visual language model | 多模态预训练模型
The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
Implementation of my RAG system that won all categories in Enterprise RAG Challenge 2
Query anything (GitHub, Notion, +40 more) with SQL and let LLMs (ChatGPT, Claude) connect to using MCP
🐉 Loong: Synthesize Long CoTs at Scale through Verifiers.
[Up-to-date] Large Language Model Agent: A Survey on Methodology, Applications and Challenges
A curated collection of LLM reasoning and planning resources, including key papers, limitations, benchmarks, and additional learning materials.