SliceGraph maps process isomers in multi-run CoT reasoning, finding that 85.5% of 954 problem-model cells show correct trajectories splitting into multiple process families with 76.6% of run pairs cross-family on average.
arXiv preprint arXiv:2510.26277 , year=
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
NeuFS selects active few-shot samples for LLMs by representing samples via neuron activation patterns and applying a dual-criteria strategy of diversity and neuron consensus to identify informative examples.
DenoiseRL optimizes recovery from noisy prefixes in weak-model reasoning failures to improve performance and self-correction on math and general reasoning benchmarks without external supervision.
citing papers explorer
-
SliceGraph: Mapping Process Isomers in Multi-Run Chain-of-Thought Reasoning
SliceGraph maps process isomers in multi-run CoT reasoning, finding that 85.5% of 954 problem-model cells show correct trajectories splitting into multiple process families with 76.6% of run pairs cross-family on average.
-
Neuron-Aware Active Few-Shot Learning for LLMs
NeuFS selects active few-shot samples for LLMs by representing samples via neuron activation patterns and applying a dual-criteria strategy of diversity and neuron consensus to identify informative examples.
-
DenoiseRL: Bootstrapping Reasoning Models to Recover from Noisy Prefixes
DenoiseRL optimizes recovery from noisy prefixes in weak-model reasoning failures to improve performance and self-correction on math and general reasoning benchmarks without external supervision.