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Gaps remain in our understanding of how large language models (LLMs) acquire knowledge during pre-training. We posit ...
Weakly-Supervised Dense Video Captioning aims to localize and describe multiple events in untrimmed videos given only...
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editi...
Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, produ...
Language-model judges now gate training data, score generations, and drive leaderboards. The judge is then a measurem...
Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remot...
As terminal-based code agents become prevalent, agent trajectories have accumulated at scale, while realistic, execut...
Evaluating physical reasoning in video models is difficult because absolute motion measurements depend on frame rate,...
Scaling interactive and verifiable environments is critical for training terminal agents. As frontier models become m...
While diffusion base models such as GPT-Image-2 and Nano-Banana exhibit remarkable visual expressiveness, their end-t...
MLLM-based embedding models remain limited in compositional retrieval, often failing to distinguish scenes containing...
On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher. E...