hanmenghan / Skip-n
This repository contains the code of our paper 'Skip \n: A simple method to reduce hallucination in Large Vision-Language Models'.
☆13Updated last year
Alternatives and similar repositories for Skip-n:
Users that are interested in Skip-n are comparing it to the libraries listed below
- [NeurIPS 2024] Calibrated Self-Rewarding Vision Language Models☆70Updated 9 months ago
- Official code for "What Makes for Good Visual Tokenizers for Large Language Models?".☆58Updated last year
- HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data (Accepted by CVPR 2024)☆44Updated 8 months ago
- Holistic Coverage and Faithfulness Evaluation of Large Vision-Language Models (ACL-Findings 2024)☆15Updated 11 months ago
- Emerging Pixel Grounding in Large Multimodal Models Without Grounding Supervision☆35Updated 5 months ago
- ☆18Updated 8 months ago
- ☆29Updated 7 months ago
- ☆24Updated 3 weeks ago
- [CVPR2024 Highlight] Official implementation for Transferable Visual Prompting. The paper "Exploring the Transferability of Visual Prompt…☆38Updated 3 months ago
- ☆19Updated last year
- TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models☆29Updated 4 months ago
- COLA: Evaluate how well your vision-language model can Compose Objects Localized with Attributes!☆24Updated 4 months ago
- Official Code Release for "Diagnosing and Rectifying Vision Models using Language" (ICLR 2023)☆33Updated last year
- VideoHallucer, The first comprehensive benchmark for hallucination detection in large video-language models (LVLMs)☆27Updated 9 months ago
- VisualGPTScore for visio-linguistic reasoning☆27Updated last year
- PyTorch code for "Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Training"☆33Updated last year
- ☆31Updated 8 months ago
- Compress conventional Vision-Language Pre-training data☆49Updated last year
- ☆17Updated last year
- [NeurIPS 2023] Official Pytorch code for LOVM: Language-Only Vision Model Selection☆20Updated last year
- [CVPR23 Highlight] CREPE: Can Vision-Language Foundation Models Reason Compositionally?☆32Updated last year
- ☆26Updated last year
- Look, Compare, Decide: Alleviating Hallucination in Large Vision-Language Models via Multi-View Multi-Path Reasoning☆20Updated 6 months ago
- [NeurIPS 2024] Official PyTorch implementation of "Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives"☆37Updated 3 months ago
- ☆22Updated 4 months ago
- Enhancing Large Vision Language Models with Self-Training on Image Comprehension.☆65Updated 9 months ago
- FreeVA: Offline MLLM as Training-Free Video Assistant☆57Updated 9 months ago
- We introduce new approach, Token Reduction using CLIP Metric (TRIM), aimed at improving the efficiency of MLLMs without sacrificing their…☆13Updated 3 months ago
- This is the official repo for Debiasing Large Visual Language Models, including a Post-Hoc debias method and Visual Debias Decoding strat…☆76Updated last month
- [Arxiv] Aligning Modalities in Vision Large Language Models via Preference Fine-tuning☆80Updated 10 months ago