KDD2026-Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans @TheOfficialACM

KDD2026-Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans @TheOfficialACM

Uploaded July 2026 | Updated September 2026, 2 weeks ago

Yu Lei, Hao Liu, Chengxing Xie, Songjia Liu, Zhiyu Yin, Canyu Chen, Guohao Li, Philip Torr, Zhen Wu

KDD2026-Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans

KDD 2026 - Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis

CAIS 2026 | Keynote: Andy Konwinski (Laude Institute)

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KDD 2026 - Strainer: Encrypted Video Traffic Identification for Mixed Segment Transmission Pattern

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KDD 2026-FedTail-DT:ADual-TeacherFramework forLong-Tailed Heterog.FLwithCLIP Protot. andAdaptiveAgg.

KDD 2026 - Beyond Language Processing: LLMs Rules-Injected Instruction Tuning for Traffic Prediction

KDD 2026: DynaTree: Dynamic Agentic Retrieval Tree for Time-Sensitive News Retrieval

KDD2026-Alignment-Free Multi-Modality Large-Small Model Bidirectional Collab. with Missing Modality

KDD 2026-MGTA: Multi-scale Graph Tokens Alignment for CTR Prediction via Pre-trained Language Models

Association for Computing Machinery (ACM) |

KDD2026-Are LLMs Socially Adaptive? Contrasting Belief Evolution in Large Language Models and Humans