Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning
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TL;DR - The paper identifies repetitive prompt copying as a widespread long-context reasoning failure caused by poor evidence grounding. Its evidence-aware RL method, GEAR, improves benchmark scores by up to 4.6 points while producing shorter, less repetitive reasoning traces.
- Repetitive copying worsens as context length increases and correlates with incorrect answers.
- GEAR rewards overlap with relevant evidence and penalizes copying from irrelevant distractors.
- An automated pipeline creates evidence-annotated training data from arbitrary documents.
- Improvements are consistent across model scales and benchmarks, with larger gains on longer contexts.
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Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning
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TL;DR - The paper identifies repetitive prompt copying as a widespread long-context reasoning failure caused by poor evidence grounding. Its evidence-aware RL method, GEAR, improves benchmark scores by up to 4.6 points while producing shorter, less repetitive reasoning traces.
- Repetitive copying worsens as context length increases and correlates with incorrect answers.
- GEAR rewards overlap with relevant evidence and penalizes copying from irrelevant distractors.
- An automated pipeline creates evidence-annotated training data from arbitrary documents.
- Improvements are consistent across model scales and benchmarks, with larger gains on longer contexts.