11 papers
When Does Pre-Trained Capacity Help Causal Learning? From Scalar Prediction to Counterfactual Post-Training
Qi Xu, Zijie Lei, Zhifei Deng +2
How does pre-trained model capacity relate to performance after adaptation for causal tasks? We study two systems built on the Qwen 2.5 family: CausalLLM, which estimates scalar po…
CURIO: Curiosity-Driven Test-Time Learning for Open-Ended Discovery
Tao Feng, Fangxu Yu, Zijie Lei +5
Open-ended discovery requires learning from repeated attempts while continuing to explore directions whose value is not yet apparent. Search with a frozen large language model (LLM…
LLMRouter: Unified Infrastructure for Developing, Evaluating, and Deploying LLM Routers
Tao Feng, Fangxu Yu, Haozhen Zhang +9
No single large language model (LLM) is optimal across all queries and budget constraints, making model routing essential for cost-effective deployment. Existing routers adopt dive…
Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting
Defu Cao, Zijie Lei, Muyan Weng +2
Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet their discrete, language-oriente…
EventConnector: Mining Social Event Relations through Temporal Graphs
Zijie Lei, Haofei Yu, Ge Liu +1
Understanding and retrieving related real-world events based on their temporal dynamics is a fundamental challenge in time-sensitive applications such as forecasting, information r…
LRanker: Scaling LLM Ranking to Millions of Candidates with Test-Time Scaling
Tao Feng, Zijie Lei, Zhigang Hua +4
Large language models (LLMs) offer strong semantic representations for ranking, but processing candidate texts within limited contexts and repeatedly invoking an LLM for candidate-…
GraphPlanner: Graph Memory-Augmented Agentic Routing for Multi-Agent LLMs
Tao Feng, Haozhen Zhang, Zijie Lei +2
LLM routing has achieved promising results in integrating the strengths of diverse models while balancing efficiency and performance. However, to support more realistic and challen…
UniRec: Unified Multimodal Encoding for LLM-Based Recommendations
Zijie Lei, Tao Feng, Zhigang Hua +5
Large language models have recently shown promise for multimodal recommendation, particularly with text and image inputs. Yet real-world recommendation signals extend far beyond th…
TinyScientist: An Interactive, Extensible, and Controllable Framework for Building Research Agents
Haofei Yu, Keyang Xuan, Fenghai Li +6
Automatic research with Large Language Models (LLMs) is rapidly gaining importance, driving the development of increasingly complex workflows involving multi-agent systems, plannin…
FusionFactory: Fusing LLM Capabilities with Multi-LLM Log Data
Tao Feng, Haozhen Zhang, Zijie Lei +5
The rapid advancement of large language models (LLMs) has created a diverse landscape of models, each excelling at different tasks. This diversity drives researchers to employ mult…
R1-Ranker: Teaching LLM Rankers to Reason
Tao Feng, Zhigang Hua, Zijie Lei +4
Large language models (LLMs) have recently shown strong reasoning abilities in domains like mathematics, coding, and scientific problem-solving, yet their potential for ranking tas…