Papers with perceptual quality
AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling (2026.findings-acl)
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| Challenge: | Existing codecs optimize acoustic reconstruction, leaving emotion expressiveness insufficiently modeled at the representation level. |
| Approach: | They propose an emotion-guided neural speech codec that preserves emotional information while maintaining semantic fidelity and prosodic naturalness. |
| Outcome: | The proposed codec preserves emotional cues while maintaining semantic fidelity and prosodic naturalness. |
Holistic Evaluation for Interleaved Text-and-Image Generation (2024.emnlp-main)
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| Challenge: | Existing evaluation benchmarks do not support arbitrarily interleaved images and text for both inputs and outputs. |
| Approach: | They propose to use a benchmark to evaluate interleaved text-and-image generation . they define five evaluation aspects for InterleavatedEval, a reference-free metric . |
| Outcome: | The proposed benchmarks cover a limited number of domains and use cases and lack comparableity-based metrics. |
OSCBench: Benchmarking Object State Change in Text-to-Video Generation (2026.acl-long)
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Xianjing Han, Bin Zhu, Shiqi Hu, Franklin Mingzhe Li, Patrick Carrington, Roger Zimmermann, Jingjing Chen
| Challenge: | Existing benchmarks focus on perceptual quality, text–video alignment, or physical plausibility, leaving a critical aspect of action understanding unexplored. |
| Approach: | They introduce a benchmark specifically designed to assess OSC performance in T2V models. |
| Outcome: | The proposed benchmark assesses the performance of open-source and proprietary T2V models on object state change (OSC) in the context of novel and compositional scenarios. |