Equal Path Cost, Unequal Output Effects: Understanding Perturbation Propagation in Diffusion Models
Wei Guo et al.
#arXiv #cs.AI

Equal Path Cost, Unequal Output Effects: Understanding Perturbation Propagation in Diffusion Models
Wei Guo et al.
#arXiv #cs.AI
When Lower Reconstruction Loss Hurts: Distributionally Robust Refinement for Low-Bit LLM Quantization
Yanlong Zhao et al.
#arXiv #cs.AI #cs.LG #stat.ML
When Interfaces Speak: Data-Aware Generative UI Harness for Active Interaction
Xiaolong Li et al.
#arXiv #cs.AI
Agent-Controlled Forgetting for Tool-Using Agents: Reversible Context Curation in Practice
Jan-Peter Franke
#arXiv #cs.AI
New arXiv work uses probability signatures to explain how two-layer networks learn modular addition, linking gradient dynamics to discrete Fourier structure and clarifying early-loss behavior under label noise.
#MachineLearning #DeepLearning #Interpretability #ArXiv
https://arxiv.org/abs/2610.11833
GeoReform: Reflective Formalization Evolution for Multimodal Geometry Problem Solving
Jialu Wang et al.
#arXiv #cs.AI
A Structural Theory of Cognitive Representation and Problem Solving,Contexts, Invariance, and the Knowledge Space
Antal Jakov\'ac, Andr\'as Telcs
#arXiv #cs.AI
Use and Disuse: Intent-Structured Experience Consolidation for Memory and Learning in LLM Agents
Xiangyi Zeng et al.
#arXiv #cs.AI
Complexity of Grounded Semantics and Preferred Semantics in Finitary Argumentation Frameworks
Jinfan Xu, Jieting Luo
#arXiv #cs.AI #cs.LO
An Interpretable Approach to PDE Solution Discovery via Structural Experience Distillation
Yunpeng Gong et al.
#arXiv #cs.AI
Error-Propagation Modeling for Failure Attribution in LLM-Based Multi-Agent Systems
Jiaqi Liao et al.
#arXiv #cs.AI
Cognition-Oriented Emotion Tracing from Causes to Consequences in Real-World Social Scenes
Hao Li et al.
#arXiv #cs.AI
On the Clock: Towards Punctual and Productive Time-Budgeted AI Agents
Aaron Wang et al.
#arXiv #cs.AI #cs.LG
New arXiv paper proposes a 3D framework characterizing AI puzzle-solving methods via MDP formalism, autonomy, and computational cost, comparing Neurosolver, FBRL, and an LLM-based approach. Useful lens for evaluating…
#AI #ReinforcementLearning #LLMs #Arxiv
https://arxiv.org/abs/2610.11696