activity
20192026
most citedModeling emotion in complex stories: the Stanford Emotional Narratives Dataset

84 citations · 182 across the 24 of their papers we have counts for

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Showing 2026 · cs.AIShow all

6 papers · 2 filters

cs.AI2026

From Memory to Guide: Spatio-Temporal Composer for Procedural Coding Memory

Zhixuan Tan, Pengjie Gu, Zhao Li +4

Memory-augmented agents typically integrate procedural knowledge by injecting retrieved skills directly into text prompts. This approach dangerously equates readable text with reli…

cs.AI2026

Rational Clarification by Assistive Agents via Value-of-Information Reasoning

T. Duy Nguyen-Hien, Yee Whye Teh, Wee Sun Lee +1

Users of language-based assistive agents often make ambiguous requests. In response, an assistant can either directly act on its interpretation of the request --- risking misalignm…

cs.AI2026

CogGym: Towards Large-Scale Comparative Evaluation of Human and Machine Cognition

Lance Ying, Jinzhou Wu, Yingshan Susan Wang +53

Understanding and modeling human intelligence are parallel goals shared by artificial intelligence (AI) and cognitive science. As AI systems grow increasingly capable, in what ways…

cs.AI2026

Evaluating Rational Contracting in Natural Language

Bhavyesh Sajja, Max Kleiman-Weiner, Roger Zimmermann +1

The emergence of language-based AI agents promises to transform the scope of machine economic activity. Instead of just proposing bids or following hard-coded protocols, such agent…

cs.AI2026

ConMem: Structured Memory-Guided Adaptation in Training-Free Multi-Agent Systems

Zhixun Tan, Qiang Chen, Tairan Huang +2

Recent advances have improved the adaptive capabilities of LLM-based multi-agent systems (MAS) through memory-, skill-, and learning-based approaches, yet these approaches remain c…

cs.AI2026

An Enigma of Artificial Reason: Investigating the Production-Evaluation Gap in Large Reasoning Models

Mingzhong Sun, Teresa Yeo, Armando Solar-Lezama +1

Studies of human reasoning have shown that people are typically stronger at evaluating reasoning than producing it from scratch. In contrast, large reasoning models (LRMs) are trai…