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Cross-domain experiments show that the learned scorer transfers across benchmarks, indicating that the method captures reusable joingraph traversal behavior.
This work introduces Scientific Introduction Generation (SciIG), a task that evaluates LLMs'ability to produce coherent introductions from titles, abstracts, and related works, and combines automated metrics with LLM-as-a-judge evaluations.
This work proposes RSF-GLLM, a framework decoupling differentiable graph reasoning from answer generation, and introduces flow sparsity regularization to theoretically guarantee convergence from soft probabilities to discrete reasoning paths.
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