Reasoning depth, retrieval-aware inference and uncertainty-aware decoding [developing] [developing] [developing] [developing]
Key Questions
What is Cog-DRIFT?
Cog-DRIFT fixes RLVR stalls using scaffolding and zero-reward learning. It breaks exploration barriers in hard reasoning tasks.
What does ARC-AGI-3 or ViGoR evaluate?
ARC-AGI-3 and ViGoR-Bench test reasoning depth in visual and general models. They reveal limits in latent planning discovery.
What is the Depth Ceiling in LLMs?
The Depth Ceiling limits LLMs in discovering latent planning structures. Stanford/MIT studies show harnesses boost performance 6x with agents.
What patterns show in tool-integrated reasoning?
Tool-integrated reasoning reveals inefficiency patterns beyond accuracy. Studies decompose gains in multi-LLM pipelines.
What is the 70-page RM on mathematical objects?
Weston's 70-page paper covers reasoning over mathematical objects. It advances symbolic and structured reasoning benchmarks.
How does context affect LLM reasoning?
Context silently shortens LLM reasoning depth, as per Reasoning Shift. It impacts chain-of-thought faithfulness (87%/29%).
What is FIPO or LightThinker++?
FIPO and LightThinker++ address uncertainty-aware decoding and retrieval. They improve inference with scaffolding and symbolic aids.
Why emphasize symbolic approaches like Chollet/Marcus?
Chollet and Marcus advocate symbolic reasoning over curve-fitting. It counters limitations in pure scaling for deep reasoning.
Stanford/MIT Harnesses 6x/agent surveys; ARC-AGI-3/ViGoR; Cog-DRIFT RLVR stall fix via scaffolding; Erdős; Weston 70pg RM; CoT faith 87%/29%; FIPO/Qworld; LightThinker++; Chollet/Marcus symbolic; tool-integrated inefficiency patterns.