before_sent:  It corrects beam search step-by-step via the optimal attention distribution to make the generated text attend to source tokens in a controlled way. Experiments show the proposed attention-aware inferenceproduces summaries rather differently from the beam search , and achieves promising improvements of higher scores and greater conciseness.
before_sent_with_intent: <meaning-changed>  It corrects beam search step-by-step via the optimal attention distribution to make the generated text attend to source tokens in a controlled way. Experiments show the proposed attention-aware inferenceproduces summaries rather differently from the beam search , and achieves promising improvements of higher scores and greater conciseness.
after_sent:  It corrects beam search step-by-step via the optimal attention distribution to stipulate how a global optimal hypothesis should attend to the source. A global scoring function is then developed to regulate beam search to generate summaries in a more near-global optimal fashion. This novel design enjoys a distinctive property, i.e. the global attention distribution could be predicted before inference, enabling stepwise improvements on the beam search , and achieves promising improvements of higher scores and greater conciseness.