Recent alternatives include agentic reasoning through code or tool calls, and latent reasoning with learnable hidden embeddings.

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• One word is enough for both agentic and latent visual reasoning.claim0.795
  The paper's thesis from the title.
• Agentic methods incur context-switching latency from external execution.claim0.774
  Identifies a key limitation of agentic methods.
• One word is enough for both agentic operation and latent reasoning unitconcept0.765
  Core idea of ATLAS: a single discrete token serves dual purpose of operation specification and latent reasoning.
• ATLAS: Agentic or Latent Visual Reasoningframework0.762
  Core framework proposing discrete functional tokens as a unified solution for visual reasoning in VLMs, bridging agentic and latent approaches.
• Natural Language Autoencoders achieve readable explanations through unsupervised reconstruction loss optimized with reinforcement learning, not explicit interpretability constraints.claim0.757
  Core insight: reconstruction objective combined with appropriate initialization and KL regularization produces human-interpretable explanations as emergent property.
• Latent methods lack task generalization and are difficult to train with autoregressive parallelization.claim0.756
  Identifies key limitations of latent methods.
• Agentic Visual Reasoningconcept0.750
  Paradigm where VLM acts as controller generating code or tool calls to external modules for visual operations, incurring context-switching latency.
• ATLAS combines the strengths of agentic and latent reasoning by using a single discrete word (functional token) that serves both roles.claim0.747
  Core claim of the paper: a unified token bridges the gaps.