most cited"My agent understands me better": Integrating Dynamic Human-like Memory Recall and Consolidation in LLM-Based Agents

26 citations · 27 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC2026

Blur Effects on User Performance in Target-Pointing Tasks

Ryuto Tomihari, Taiki Kinoshita, Yosuke Oba +2

In projectors and head-mounted displays, an out-of-focus image appears blurred. Even when a display itself is in focus, computer operation may be hindered if the display is far fro…

cs.HC2026

Skewed Dual Normal Distribution Model: Predicting Touch Pointing Success Rates for Targets Near Screen Edges and Corners

Nobuhito Kasahara, Shota Yamanaka, Homei Miyashita

Typical success-rate prediction models for tapping exclude targets near screen edges. However, design constraints often force such placements, and in scrollable user interfaces, an…

cs.HC2026★ 1 cited

Skewed Dual Normal Distribution Model: Predicting 1D Touch Pointing Success Rate for Targets Near Screen Edges

Nobuhito Kasahara, Shota Yamanaka, Homei Miyashita

Typical success-rate prediction models for tapping exclude targets near screen edges; however, design constraints often force such placements. Additionally, in scrollable UIs any e…

cs.HC2026

A Tool for Estimating Success Rates of Raycasting-Based Object Selection in Virtual Reality

Tatsuya Okuno, Haruto Shimizu, Nobuhito Kasahara +3

As XR devices become widespread, 3D interaction has become commonplace, and UI developers are increasingly required to consider usability to deliver better user experiences. The HC…

cs.CL2024

SynapticRAG: Enhancing Temporal Memory Retrieval in Large Language Models through Synaptic Mechanisms

Yuki Hou, Haruki Tamoto, Qinghua Zhao +1

Existing retrieval methods in Large Language Models show degradation in accuracy when handling temporally distributed conversations, primarily due to their reliance on simple simil…

cs.HC2024★ 26 cited

"My agent understands me better": Integrating Dynamic Human-like Memory Recall and Consolidation in LLM-Based Agents

Yuki Hou, Haruki Tamoto, Homei Miyashita

In this study, we propose a novel human-like memory architecture designed for enhancing the cognitive abilities of large language model based dialogue agents. Our proposed architec…