Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models
On the map: LLM agents and tool use → Social simulation and multi-agent debate
Abstract (arXiv)
Assessing how well a large language model (LLM) understands human, rather than merely text, remains an open challenge. To bridge the gap, we introduce Sentient Agent as a Judge (SAGE), an automated evaluation framework that measures an LLM's higher-order social cognition. SAGE instantiates a Sentient Agent that simulates human-like emotional changes and inner thoughts during interaction, providing a more realistic evaluation of the tested model in multi-turn conversations. At every turn, the agent reasons about (i) how its emotion changes, (ii) how it feels, and (iii) how it should reply, yielding a numerical emotion trajectory and interpretable inner thoughts. Experiments on 100 supportive-dialogue scenarios show that the final Sentient emotion score correlates strongly with Barrett-Lennard Relationship Inventory (BLRI) ratings and utterance-level empathy metrics, validating psychological fidelity. We also build a public Sentient Leaderboard covering 18 commercial and open-source models that uncovers substantial gaps (up to 4x) between frontier systems (GPT-4o-Latest, Gemini2.5-Pro) and earlier baselines, gaps not reflected in conventional leaderboards (e.g., Arena). SAGE thus provides a principled, scalable and interpretable tool for tracking progress toward genuinely empathetic and socially adept language agents.
Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 56 of its 75 references that are in the map. First posted on arXiv 1 May 2025.
Builds on
56 of 75 references.
Closest ancestors · 4
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- 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate30 May
Other references · 52
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Citing papers per year: 2025: 5; 2026: 16.
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- 2026EMPA: Evaluating Persona-Aligned Empathy as a Process28 Feb 2026
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- 2025RecGPT-V2 Technical Report16 Dec 2025
- 2025Too Good to be Bad: On the Failure of LLMs to Role-Play Villains7 Nov 2025
- 2025Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey2 Oct 2025
- 2025PEER: Unified Process-Outcome Reinforcement Learning for Structured Empathetic Reasoning13 Aug 2025
- 2025RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents3 Jul 2025
- 2025RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agentscited by 25
- 2026Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learningcited by 9
- 2025Enhancing Large Language Model Reasoning with Reward Models: An Analytical Surveycited by 8
- 2026Think Fast and Slow: Step-Level Cognitive Depth Adaptation for LLM Agentscited by 5
- 2026EIBench: A Simulator-Based Benchmark and Turn-Credit RL for Emotion Managementcited by 3
- 2025PEER: Unified Process-Outcome Reinforcement Learning for Structured Empathetic Reasoningcited by 2
- 2026User-Aware Active Knowledge Acquisition for Emotional Support Dialoguecited by 0
- 2026The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modescited by 0
- 2026Towards High-Level Semantic Intelligencecited by 0
- 2026R3-Bench: LLMs Struggle with Resource-Rational Reasoning under Shared Budgetscited by 0
- 2026R3-Bench: LLMs Struggle with Resource-Rational Reasoning under Shared Budgets17 Aug 2026
- 2026Towards High-Level Semantic Intelligence27 Jul 2026
- 2026EIBench: A Simulator-Based Benchmark and Turn-Credit RL for Emotion Management14 Jun 2026
- 2026The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes9 Jun 2026
- 2026User-Aware Active Knowledge Acquisition for Emotional Support Dialogue28 May 2026
- 2026Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning8 Apr 2026
- 2026Think Fast and Slow: Step-Level Cognitive Depth Adaptation for LLM Agents13 Feb 2026
- 2025Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey2 Oct 2025
- 2025PEER: Unified Process-Outcome Reinforcement Learning for Structured Empathetic Reasoning13 Aug 2025
- 2025RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents3 Jul 2025
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- 2026Can You Break RLVER? Probing Adversarial Robustness of RL-Trained Empathetic Agentscited by 0
- 2026Can You Break RLVER? Probing Adversarial Robustness of RL-Trained Empathetic Agents8 May 2026
- 2026Agent-as-a-Judge8 Jan 2026
- 2025Too Good to be Bad: On the Failure of LLMs to Role-Play Villainscited by 11
- 2025RecGPT-V2 Technical Reportcited by 8
- 2026EMPA: Evaluating Persona-Aligned Empathy as a Processcited by 4
- 2026MICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialoguecited by 3
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- 2026TRACER: Trajectory-Aligned Learning for Multi-Turn User Simulationcited by 0
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- 2026COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning31 Aug 2026
- 2026MICA: Multi-granularity Intertemporal Credit Assignment for Long-Horizon Emotional Support Dialogue6 Mar 2026
- 2026EMPA: Evaluating Persona-Aligned Empathy as a Process28 Feb 2026
- 2025RecGPT-V2 Technical Report16 Dec 2025
- 2025Too Good to be Bad: On the Failure of LLMs to Role-Play Villains7 Nov 2025
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