lilvjosephtang/SEAM-Benchmark
SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models CSSLab, Department of Computer Science, University of Toronto[COLM '25] Second Conference on Language Modeling Paper: Paper Project Page / Leaderboard: SEAM Benchmark Code: GitHub Abstract Evaluating whether vision-language models (VLMs) reason consistently across representations is challenging because modality comparisons are typically confounded by task differences and… See the full description on the dataset page: https://huggingface.co/datasets/lilvjosephtang/SEAM-Benchmark.
| Author / organization | lilvjosephtang |
|---|---|
| License (as declared) | cc-by-nc-4.0 |
| Downloads | 259 (as reported by Hugging Face) |
| Likes | 9 |
| Created | 19 August 2025 |
| Last updated at source | 2 September 2025 |
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Recent changes
- 17 Oct 2026 Description: SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models CSSLab, Department of Computer Science, University of Toronto[COLM '25] Second Conference on Language Modeling Paper: Paper Project Page / Leaderboard: SEA → SEAM: Semantically Equivalent Across Modalities Benchmark for Vision-Language Models CSSLab, Department of Computer Science, University of Toronto[COLM '25] Second Conference on Language Modeling Paper: Paper Project Page / Leaderboard: SEA
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