2 citations · 5 across the 8 of their papers we have counts for
9 papers
TRACER: Trajectory-Aligned Learning for Multi-Turn User Simulation
Geng Chen, Ruotong Pan, Zhirui Yang +9
Faithful user simulation is fundamental to building, evaluating, and improving interactive AI at scale. Yet current simulators often produce plausible individual responses without…
PraMem: Practice-derived Experiential Memory for Long-horizon Behavior Prediction
Zhuoqun Li, Boxi Cao, Jiawei Chen +11
Long-horizon behavior prediction aims to infer a user's next action based on a lengthy historical sequence, playing a crucial role in artificial intelligence field. The rise of lar…
MetaphorVU: Towards Metaphorical Video Understanding
Zhuoqun Li, Boxi Cao, Guiping Jiang +13
Metaphorical videos are prevalent across various real-world scenarios to convey complex ideas, and understanding them typically requires high-order cognitive capabilities. The lack…
Towards Real-world Human Behavior Simulation: Benchmarking Large Language Models on Long-horizon, Cross-scenario, Heterogeneous Behavior Traces
Jiawei Chen, Ruoxi Xu, Boxi Cao +12
The emergence of Large Language Models (LLMs) has illuminated the potential for a general-purpose user simulator. However, existing benchmarks remain constrained to isolated scenar…
GoLongRL: Capability-Oriented Long Context Reinforcement Learning with Multitask Alignment
Minxuan Lv, Tiehua Mei, Tanlong Du +9
We present GoLongRL, a fully open-source, capability-oriented post-training recipe for long-context reinforcement learning with verifiable rewards (RLVR). Existing long-context RL…
Unlocking Exploration in RLVR: Uncertainty-aware Advantage Shaping for Deeper Reasoning
Can Xie, Ruotong Pan, Xiangyu Wu +4
Reinforcement Learning with Verifiable Rewards (RLVR) has shown significant promise for enhancing the reasoning capabilities of large language models (LLMs). However, prevailing al…
Beyond Correctness: Benchmarking Multi-dimensional Code Generation for Large Language Models
Jiasheng Zheng, Boxi Cao, Zhengzhao Ma +5
In recent years, researchers have proposed numerous benchmarks to evaluate the impressive coding capabilities of large language models (LLMs). However, current benchmarks primarily…
Not All Contexts Are Equal: Teaching LLMs Credibility-aware Generation
Ruotong Pan, Boxi Cao, Hongyu Lin +5
The rapid development of large language models has led to the widespread adoption of Retrieval-Augmented Generation (RAG), which integrates external knowledge to alleviate knowledg…
AI for social science and social science of AI: A Survey
Ruoxi Xu, Yingfei Sun, Mengjie Ren +5
Recent advancements in artificial intelligence, particularly with the emergence of large language models (LLMs), have sparked a rethinking of artificial general intelligence possib…