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Next-ToBE

3 articles · Page 1 of 1

Jun 18, 2026 · Artificial Intelligence

Why Large Language Models Are Short‑Sighted and How Next‑ToBE Unlocks Anticipatory Reasoning

The article examines the short‑sighted nature of current next‑token prediction in LLMs, presents the Next‑ToBE (Next Token‑Bag Exploitation) method that reshapes the training objective to expose latent future‑token awareness, and shows through extensive experiments that this approach improves anticipatory reasoning and downstream task performance.

Anticipatory ReasoningFuture Token PredictionLLM evaluation

0 likes · 12 min read

Why Large Language Models Are Short‑Sighted and How Next‑ToBE Unlocks Anticipatory Reasoning

Machine Learning Algorithms & Natural Language Processing

May 25, 2026 · Artificial Intelligence

Next-ToBE: Enabling Overconfident LLMs to See Further and Reason More Accurately

The ICLR 2026 paper introduces Next‑ToBE, a training‑objective modification that replaces the one‑hot next‑token label with a soft distribution over a future token window, unlocking latent foresight in LLMs, improving future‑token hit rate, downstream reasoning performance, and reducing training memory and time.

Future Token PredictionLarge Language ModelsNext-ToBE

0 likes · 12 min read

Next-ToBE: Enabling Overconfident LLMs to See Further and Reason More Accurately

Machine Learning Algorithms & Natural Language Processing

May 21, 2026 · Artificial Intelligence

Can a New Training Objective Make LLMs See Further and Reason Better?

The paper introduces Next‑ToBE, a training‑objective modification that replaces the one‑hot next‑token label with a soft distribution covering a future token window, thereby activating latent anticipatory capacity in large language models and yielding significant gains in token‑hit rates, reasoning accuracy, and training efficiency.

Anticipatory CapacityLarge Language ModelsNext-ToBE

0 likes · 11 min read

Can a New Training Objective Make LLMs See Further and Reason Better?