CLIPScore uses a web-pretrained CLIP model to evaluate image captions without references and achieves higher human correlation than CIDEr or SPICE.
Evaluating clip: towards characterization of broader capabilities and downstream implications.arXiv preprint arXiv:2108.02818
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VideoABC estimates video-LLM failure probability via low-dimensional attribute projection, dual quantization (k-means plus lattice), and psychophysics-inspired synthetic data.
Reward models used as quality scorers in text-to-image generation encode demographic biases that cause reward-guided training to sexualize female subjects, reinforce stereotypes, and reduce diversity.
ComMem proposes complementary fast visual cache and slow textual prototype memories for test-time adaptation of VLMs, claiming superior performance on 15 benchmarks under distribution shifts.
citing papers explorer
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CLIPScore: A Reference-free Evaluation Metric for Image Captioning
CLIPScore uses a web-pretrained CLIP model to evaluate image captions without references and achieves higher human correlation than CIDEr or SPICE.
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An Attribute-Based Measure of Video Complexity
VideoABC estimates video-LLM failure probability via low-dimensional attribute projection, dual quantization (k-means plus lattice), and psychophysics-inspired synthetic data.
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Bias at the End of the Score
Reward models used as quality scorers in text-to-image generation encode demographic biases that cause reward-guided training to sexualize female subjects, reinforce stereotypes, and reduce diversity.
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ComMem: Complementary Memory Systems for Test-Time Adaptation of Vision-Language Models
ComMem proposes complementary fast visual cache and slow textual prototype memories for test-time adaptation of VLMs, claiming superior performance on 15 benchmarks under distribution shifts.