Papers with scalable data synthesis pipeline
WebSTAR: Scalable Data Synthesis for Computer Use Agents with Step-Level Filtering (2026.acl-long)
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| Challenge: | Existing datasets rely on human demonstrations, limiting scalability. |
| Approach: | They propose a scalable data synthesis pipeline that transforms noisy rollouts into reliable supervision without human annotation. |
| Outcome: | The proposed pipeline transforms noisy rollouts into reliable supervision without human annotation. |
MVP: Enhancing Video Large Language Models via Self-supervised Masked Video Prediction (2026.acl-long)
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| Challenge: | Recent research has attempted to transfer reinforcement learning paradigms to Video Large Language Models (MLLMs) but these methods lack explicit supervision for intrinsic temporal coherence and inter-frame correlations. |
| Approach: | They propose a novel post-training objective: Masked Video Prediction (MVP) that requires the model to reconstruct a masked continuous segment from a set of challenging distractors and employs Group Relative Policy Optimization (GRPO) with a fine-grained reward function to enhance the model's understanding of video context and temporal properties. |
| Outcome: | The proposed model improves video reasoning capabilities by reinforcing temporal reasoning and causal understanding. |