A synthetic pipeline creates and internalizes reasoning traces in VLMs for long-context visual document understanding, with a 32B model surpassing a 235B model on MMLongBenchDoc and showing 12.4x fewer output tokens.
Chain-of-thought tokens are computer program variables
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
KG-Hopper uses RL to embed full multi-hop KG traversal and backtracking into a single LLM inference round, enabling a 7B model to outperform larger multi-step systems and compete with GPT-3.5/GPT-4o-mini on eight benchmarks.
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Internalized Reasoning for Long-Context Visual Document Understanding
A synthetic pipeline creates and internalizes reasoning traces in VLMs for long-context visual document understanding, with a 32B model surpassing a 235B model on MMLongBenchDoc and showing 12.4x fewer output tokens.
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KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning
KG-Hopper uses RL to embed full multi-hop KG traversal and backtracking into a single LLM inference round, enabling a 7B model to outperform larger multi-step systems and compete with GPT-3.5/GPT-4o-mini on eight benchmarks.