SemComp-Bench: Benchmarking Semantic Task Completion in Video Generation
We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formula...
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We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formula...
Physical interaction quality is central to deformable-object manipulation, yet most benchmarks evaluate task success ...
JEPA-style latent world models can use Euclidean distance to a goal latent as the cost for model-predictive control (...
Embodied agents are increasingly used to close the gap left by end-to-end policy models. Yet the agentic path has not...
Recent advances in foundation models have enabled AI scientists to automate increasingly complete research workflows,...
High-quality creative writing data for large language models (LLMs) remains dominated by story-centric data, limiting...
Reinforcement learning (RL) has emerged as a powerful approach for improving reasoning in language and vision-languag...
Token-level hallucination detectors score each token independently from a single signal, and fail exactly when the ge...
Popular facts are memorised more deeply during pretraining and resist removal longer than rare ones, yet existing LLM...
Agent frameworks increasingly package procedural knowledge as skills: instruction files an agent reads on demand, whi...
Electrocardiography (ECG), photoplethysmography (PPG), and phonocardiography (PCG) provide complementary views of the...
We introduce PTXBench, a benchmark for evaluating and adapting large language models (LLMs) to use architecture-speci...