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From the 2 of 24 linked papers with an AI index.

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20242026
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cs.CL2026

MemUse: Moving Memory Evaluation from Direct QA to Natural Integration in Long-Term Human-AI Conversation

Ryuichi Sumida, Koji Inoue, Tatsuya Kawahara

Memory systems for conversational LLMs are conventionally evaluated by direct, fact-seeking questions about prior dialogue (Direct QA): can the model recall fact X from a prior con…

cs.CL2026

On the Structure of Address in Multi-Party Dialogue: From Discrete Labels to Continuous Levels

Taiga Mori, Koji Inoue, Divesh Lala +1

In multi-party dialogues between a dialogue system and multiple users, identifying to whom an utterance is addressed is a key challenge. Prior work has typically treated addressee…

cs.CL2026

I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System

Zi Haur Pang, Yahui Fu, Koji Inoue +1

Emotional validation - explicitly acknowledging that a user's feelings make sense - has proven therapeutic value but has received little computational attention. Emotional validati…

cs.CL2026

Toward Signing Activity Projection in Sign Language Interaction

Takao Obi, Wang Yusong, Koji Inoue +1

Social robots must interact robustly not only with users assumed by speech-centered systems but also with diverse users whose communication relies on different modalities, e.g., si…

cs.CL2026

Emotion Transcription in Conversation: A Benchmark for Capturing Subtle and Complex Emotional States through Natural Language

Yoshiki Tanaka, Ryuichi Uehara, Koji Inoue +1

Emotion Recognition in Conversation (ERC) is critical for enabling natural human-machine interactions. However, existing methods predominantly employ categorical or dimensional emo…

cs.CL20251 cited

Enhancing Long-term RAG Chatbots with Psychological Models of Memory Importance and Forgetting

Ryuichi Sumida, Koji Inoue, Tatsuya Kawahara

While Retrieval-Augmented Generation (RAG) has shown promise in enhancing long-term conversations, the increasing memory load as conversations progress degrades retrieval accuracy.…