4 citations · 4 across the 16 of their papers we have counts for
16 papers
ZenGen: Social Mind for LLMs
ZenGen Team, Ao Xiang, Bi Jingping +57
As large language models move from isolated task solving toward long-term service in human environments, they require social intelligence: the ability to infer mental states, track…
ActiveMem: Distributed Active Memory for Long-Horizon LLM Reasoning
Yunhan Jiang, Wenbin Duan, Shasha Guo +3
Memory is essential for enabling large language model (LLM) agents to handle long-horizon reasoning tasks. Existing memory mechanisms are largely centralized, typically organizing…
Latent-GRPO: Group Relative Policy Optimization for Latent Reasoning
Jingcheng Deng, Zihao Wei, Liang Pang +4
Latent reasoning offers a more efficient alternative to explicit reasoning by compressing intermediate reasoning into continuous representations and substantially shortening reason…
Towards Robust Process Reward Modeling via Noise-aware Learning
Bin Xie, Bingbing Xu, Xueyun Tian +2
Process Reward Models (PRMs) have achieved strong results in complex reasoning, but are bottlenecked by costly process-level supervision. A widely used alternative, Monte Carlo Est…
Do We Always Need Query-Level Workflows? Rethinking Agentic Workflow Generation for Multi-Agent Systems
Zixu Wang, Bingbing Xu, Yige Yuan +2
Multi-Agent Systems (MAS) built on large language models typically solve complex tasks by coordinating multiple agents through workflows. Existing approaches generates workflows ei…
ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding
Xueyun Tian, Wei Li, Bingbing Xu +3
Recent Omni-multimodal Large Language Models show promise in unified audio, vision, and text modeling. However, streaming audio-video understanding remains challenging, as existing…
Beyond Entangled Planning: Task-Decoupled Planning for Long-Horizon Agents
Yunfan Li, Bingbing Xu, Xueyun Tian +2
Recent advances in large language models (LLMs) have enabled agents to autonomously execute complex, long-horizon tasks, yet planning remains a primary bottleneck for reliable task…
Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization
Xueyun Tian, Minghua Ma, Bingbing Xu +6
Supervised fine-tuning (SFT) on chain-of-thought (CoT) trajectories demonstrations is a common approach for enabling reasoning in large language models. Standard practices typicall…
Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents
Xiucheng Xu, Bingbing Xu, Xueyun Tian +4
External memory systems are pivotal for enabling Large Language Model (LLM) agents to maintain persistent knowledge and perform long-horizon decision-making. Existing paradigms typ…
ACE-Align: Attribute Causal Effect Alignment for Cultural Values under Varying Persona Granularities
Jiatang Luo, Bingbing Xu, Rongxin Chen +5
Ensuring that large language models (LLMs) reflect diverse cultural values is important for globally deployed NLP systems. However, existing approaches often treat cultural groups…
RPO: Decoupling Rollout and Inference Policies for LLM Reasoning
Jingchu Wang, Bingbing Xu, Yige Yuan +4
Existing reinforcement learning methods for LLM reasoning implicitly assume that the policy generating training trajectories should coincide with the one producing inference respon…
HAG: Hierarchical Demographic Tree-based Agent Generation for Topic-Adaptive Simulation
Rongxin Chen, Tianyu Wu, Bingbing Xu +3
High-fidelity agent initialization is crucial for credible Agent-Based Modeling across diverse domains. A robust framework should be Topic-Adaptive, capturing macro-level joint dis…
GIFT: Games as Informal Training for Generalizable LLMs
Nuoyan Lyu, Bingbing Xu, Xueyun Tian +6
Recent LLMs excel at formal tasks such as mathematical reasoning and code generation, but still struggle with broader abilities such as planning, creativity, and social intelligenc…
Multi-Personality Generation of LLMs at Decoding-time
Rongxin Chen, Yunfan Li, Yige Yuan +2
Multi-personality generation for LLMs, enabling simultaneous embodiment of multiple personalization attributes, is a fundamental challenge. Existing retraining-based approaches are…
From Outcomes to Processes: Guiding PRM Learning from ORM for Inference-Time Alignment
Bin Xie, Bingbing Xu, Yige Yuan +2
Inference-time alignment methods have gained significant attention for their efficiency and effectiveness in aligning large language models (LLMs) with human preferences. However,…
MIGE: Mutually Enhanced Multimodal Instruction-Based Image Generation and Editing
Xueyun Tian, Wei Li, Bingbing Xu +3
Despite significant progress in diffusion-based image generation, subject-driven generation and instruction-based editing remain challenging. Existing methods typically treat them…