Papers with RL training framework
NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning (2026.acl-long)
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| Challenge: | Neologism-aware machine translation aims to translate source sentences containing neologismes into target languages. |
| Approach: | They propose an agentic framework for neologism-aware machine translation equipped with a Wiktionary-based search toolkit. |
| Outcome: | The proposed framework is based on a Wiktionary-based search toolkit and a dedicated dataset for neologism-aware machine translation. |
ReCode: Reinforcing Code Generation with Reasoning-Process Rewards (2026.acl-long)
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| Challenge: | Bringing process-level supervision into RL often neglects optimizing reasoning quality. |
| Approach: | They propose a framework for RL that integrates reasoning-process rewards with strict execution outcomes and a benchmark comprising preference pairs of superior and inferior reasoning processes. |
| Outcome: | The proposed framework outperforms the base version of ReCode by 16.1% and reaches performance comparable to GPT-4-Turbo. |