Research map / Reinforcement learning / RL from feedback
Neural Machine Translation with Adequacy-Oriented Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the adequacy-oriented discriminator and CDR orientator | RNNSearch · Zh⇒En NIST test sets (All) | BLEU: 36.76 -> 38.42 | Helped |
| Add discriminator and CDR orientator to the coverage model | RNNSearch-Coverage · Zh⇒En NIST test sets (All) | BLEU: 39.13 -> 39.81 | Helped |
| Use the RNN discriminator and CDR orientator | RNNSearch · IWSLT 2014 De⇒En | BLEU: 26.51 -> 27.79 | Helped |
| Use the RNN discriminator and CDR orientator | Transformer-Base · WMT 2014 En⇒De | BLEU: 27.30 -> 28.01 | Helped |
| Use the RNN discriminator and CDR orientator | Transformer-Big · WMT 2014 En⇒De | BLEU: 28.35 -> 28.99 | Helped |
| Replace the CNN discriminator with the RNN discriminator (ablation) | RNNSearch adversarial setup · Zh⇒En NIST test sets (All) | BLEU: 37.54 vs. 37.59 | No clear effect |
| Use CDR reward instead of BLEU or chrF3 reward (ablation) | RNNSearch orientator · Zh⇒En NIST test sets (All) | BLEU: 37.44; 37.75; 38.02 | Helped |
| Add the discriminator to the CDR orientator (ablation) | RNNSearch · Zh⇒En NIST test sets (All) | BLEU: 38.02 -> 38.42 | Helped |
| Add the CDR orientator to the discriminator (ablation) | RNNSearch · Zh⇒En NIST test sets (All) | BLEU: 37.59 -> 38.42 | Helped |
| Add the CDR orientator without the discriminator (ablation) | Transformer-Base · WMT 2014 En⇒De | BLEU: 27.30 -> 27.80 | Helped |
| Add the RNN discriminator to the CDR orientator (ablation) | Transformer-Base · WMT 2014 En⇒De | BLEU: 27.80 -> 28.01 | Helped |
| Add the CDR orientator without the discriminator (ablation) | Transformer-Big · WMT 2014 En⇒De | BLEU: 28.35 -> 28.63 | Helped |
Closest papers by meaning
- On the Weaknesses of Reinforcement Learning for Neural Machine Translation (ICLR 2020 · similarity 0.90)
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- Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference (NeurIPS 2025 · similarity 0.86)
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- A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models (ICLR 2024 · similarity 0.85)
- SimulPL: Aligning Human Preferences in Simultaneous Machine Translation (ICLR 2025 · similarity 0.85)
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