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This position paper argues that interpretability research should be evaluated based on actionability—the extent to which insights enable concrete decisions and interventions. The authors propose a framework with evaluation criteria aligned with practical outcomes to address the lack of real-world impact in current interpretability work.
This paper identifies the 'Massive Emergence Layer' where extreme activations in LLMs originate and propagate, proposing a method to mitigate their rigidity and improve model performance on tasks like math reasoning and instruction following.
This paper introduces a new paradigm for universal Gene Regulatory Network (GRN) inference using single-cell foundation models, proposing Virtual Value Perturbation and Gradient Trajectory methods to distill regulatory knowledge.
This paper introduces the Safety-Aware Denoiser (SAD), a framework for integrating safety constraints into text diffusion models during the denoising process. It aims to reduce unsafe generations while preserving quality, addressing a gap in safety research for non-autoregressive models.
This paper provides a theoretical analysis explaining why deterministic DDIM samplers hallucinate more than stochastic DDPM samplers in diffusion models, attributing it to getting stuck in mode-interpolation regions during reverse dynamics.
This solo-author ICML paper introduces Amortized Group Relative Policy Optimization (AGRPO) to enable effective reinforcement learning post-training for diffusion language models.
This research paper analyzes the internal mechanics of Large Vision-Language Models (LVLMs) using information theory, revealing that attention mechanisms may be redundant while Feed-Forward Networks drive semantic innovation. The authors demonstrate that replacing learned attention weights with random values can yield comparable performance, suggesting current models 'get lost in attention'.
A researcher discusses their ICML 2026 paper review experience where a reviewer increased their score during rebuttal but then decreased it again, expressing concern about rejection prospects.