https://github.com/latuanvinh1998/kgalign
공식 코드KGAlign: Joint Semantic-Structural Knowledge Encoding for Multimodal Fake News Detection
Papers with Code 아카이브
Multimodal Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Reasoning over multimodal inputs.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lbotirx/cofipara
공식 코드https://github.com/lee-lab558/iava
공식 코드Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
https://github.com/leon1207/video-rag-master
공식 코드Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension
https://github.com/llm-lab-org/multimodal-rag-survey
공식 코드Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation
https://github.com/lsplx/vetesting
공식 코드VEglue: Testing Visual Entailment Systems via Object-Aligned Joint Erasing
https://github.com/lukeforeveryoung/qrnet
공식 코드https://github.com/lupantech/ScienceQA
공식 코드Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
https://github.com/m4u-benchmark/m4u
공식 코드M4U: Evaluating Multilingual Understanding and Reasoning for Large Multimodal Models
https://github.com/mac-automl/quota
공식 코드QuoTA: Query-oriented Token Assignment via CoT Query Decouple for Long Video Comprehension
https://github.com/mbzuai-oryx/agent-x
공식 코드Agent-X: Evaluating Deep Multimodal Reasoning in Vision-Centric Agentic Tasks
https://github.com/mbzuai-oryx/arb
공식 코드https://github.com/metaagentx/opencaptchaworld
공식 코드https://github.com/microsoft/MM-REACT
공식 코드MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action
https://github.com/mililab/logicocr
공식 코드LogicOCR: Do Your Large Multimodal Models Excel at Logical Reasoning on Text-Rich Images?
https://github.com/minjoong507/MPGN
공식 코드Modal-specific Pseudo Query Generation for Video Corpus Moment Retrieval
https://github.com/mitjanikolaus/multimodal-predicate-noun-dependencies
공식 코드Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?
https://github.com/mlpc-ucsd/bliva
공식 코드BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions
https://github.com/mm-thinking/metis-rise
공식 코드Metis-RISE: RL Incentivizes and SFT Enhances Multimodal Reasoning Model Learning
https://github.com/modalminds/mm-eureka
공식 코드MM-Eureka: Exploring Visual Aha Moment with Rule-based Large-scale Reinforcement Learning
https://github.com/modalminds/mm-prm
공식 코드MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision
https://github.com/modelscope/data-juicer
공식 코드MindGYM: Enhancing Vision-Language Models via Synthetic Self-Challenging Questions
https://github.com/moonshotai/kimi-vl
공식 코드https://github.com/morse-benchmark/morse-500-code
공식 코드MORSE-500: A Programmatically Controllable Video Benchmark to Stress-Test Multimodal Reasoning
https://github.com/mulab-mir/muchomusic
공식 코드MuChoMusic: Evaluating Music Understanding in Multimodal Audio-Language Models
https://github.com/nlpcode/tubench
공식 코드TUBench: Benchmarking Large Vision-Language Models on Trustworthiness with Unanswerable Questions
https://github.com/ocean-luna/hmrag
공식 코드HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented Generation
https://github.com/opendatalab/ha-dpo
공식 코드Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization
https://github.com/osilly/vision-r1
공식 코드Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
https://github.com/ouyangkun10/spacer
공식 코드https://github.com/ouyangkun10/spatial-r1
공식 코드https://github.com/p1k0pan/ICD
공식 코드Mitigating Hallucinations in Large Vision-Language Models with Instruction Contrastive Decoding
https://github.com/panasonicconnect/videomultiagents
공식 코드VideoMultiAgents: A Multi-Agent Framework for Video Question Answering
https://github.com/pbhgit/mvcd
공식 코드Language Models Can See Better: Visual Contrastive Decoding For LLM Multimodal Reasoning
https://github.com/peijin360/vsre
공식 코드https://github.com/phellonchen/DMRM
공식 코드DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.