{"total":9,"rows":[{"id":"2502.11541","title":"MuSC: Improving Complex Instruction Following with Multi-granularity Self-Contrastive Training","created":"2025-02-17","cited_by_count":12,"area":null},{"id":"2409.14195","title":"The Imperative of Conversation Analysis in the Era of LLMs: A Survey of Tasks, Techniques, and Trends","created":"2024-09-21","cited_by_count":11,"area":null},{"id":"2601.03335","title":"Digital Red Queen: Adversarial Program Evolution in Core War with LLMs","created":"2026-01-06","cited_by_count":7,"area":null},{"id":"2508.21648","title":"Leveraging Imperfection with MEDLEY A Multi-Model Approach Harnessing Bias in Medical AI","created":"2025-08-29","cited_by_count":4,"area":null},{"id":"2410.15163","title":"Optimizing Large Language Models for Dynamic Constraints through Human-in-the-Loop Discriminators","created":"2024-10-19","cited_by_count":1,"area":null},{"id":"2604.10911","title":"EvoNash-MARL: A Closed-Loop Multi-Agent Reinforcement Learning Framework for Medium-Horizon Equity Allocation","created":"2026-04-13","cited_by_count":1,"area":null},{"id":"2508.19488","title":"PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defense","created":"2025-08-27","cited_by_count":0,"area":null},{"id":"2602.02858","title":"IMAGINE: Intelligent Multi-Agent Godot-based Indoor Networked Exploration","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2603.06977","title":"NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning","created":"2026-03-07","cited_by_count":0,"area":null}],"next_cursor":null}