1 citations · 1 across the 6 of their papers we have counts for
7 papers
LOGOS: A Living Logic for AI Agent Teams That Evolve With Humans
Yuma Ichikawa, Yamato Arai, Kosaku Kimura +2
AI agents are evolving from answer engines into persistent teams that use tools, delegate work, learn from experience, and modify the artifacts that shape their future behavior. Th…
EVE-Agent: Evidence-Verifiable Self-Evolving Agents
Yamato Arai, Yuma Ichikawa
Self-evolving agents should not train on examples they cannot justify. Data-free self-evolving search agents offer a scalable route to systems that generate their own questions, an…
OneComp: One-Line Revolution for Generative AI Model Compression
Yuma Ichikawa, Keiji Kimura, Akihiro Yoshida +11
Deploying foundation models is increasingly constrained by memory footprint, latency, and hardware costs. Post-training compression can mitigate these bottlenecks by reducing the p…
Phase Transitions in a Modified Ising Spin Glass Model: A Tensor-Network-based Sampling Approach
Takumi Oshima, Yamato Arai, Koji Hukushima
Phase transitions in a modified Nishimori model, including the model considered by Kitatani, on a two-dimensional square lattice are investigated using a tensor-network-based sampl…
Quantization Error Propagation: Revisiting Layer-Wise Post-Training Quantization
Yamato Arai, Yuma Ichikawa
Layer-wise PTQ is a promising technique for compressing large language models (LLMs), due to its simplicity and effectiveness without requiring retraining. However, recent progress…
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
Yuma Ichikawa, Yamato Arai
Learning-based methods have gained attention as general-purpose solvers due to their ability to automatically learn problem-specific heuristics, reducing the need for manually craf…
Adaptive Flip Graph Algorithm for Matrix Multiplication
Yamato Arai, Yuma Ichikawa, Koji Hukushima
This study proposes the "adaptive flip graph algorithm", which combines adaptive searches with the flip graph algorithm for finding fast and efficient methods for matrix multiplica…