Temporally-Resolved Token Attribution Reveals the Generation Dynamics of Diffusion Language Models
Extends integrated-gradient attribution across layers and denoising steps to examine which inputs influence a diffusion model's developing response. Includes multi-hop graph reasoning; the authors present attribution as a complement to, not a replacement for, causal intervention.
First public: · Added to this list: October 18, 2026
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arXiv:2610.01177 · Initial submission: 2026-10-01
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Analysis and evaluation — Measure how well these methods work, investigate what their internal computation does, and identify where they fail. This includes experiments, studies of model internals, and mathematical results.
Alternative generation methods — Change how intermediate steps are generated, revised, or searched—for example, by refining several steps in parallel. These are related approaches: some still produce written chains of thought.
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