collaborators

5 papers

cs.CL2026

Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender System

Ming Li, Dai Li, Xuying Ning +10

Auto-research agents have shown the potential to automate hypothesis generation, experiment execution, and iterative refinement. However, scaling this paradigm to industry-scale re…

cs.AI2026

Inference-Time Graph Engineering for Multi-Agent LLM Workflows

Katherine Tieu, Dongqi Fu, Yinglong Xia +3

Recent multi-agent LLM systems increasingly rely on graph-structured communication to coordinate specialized agents. We revisit multi-agent orchestration from a graph-engineering p…

cs.CL2026

KVEraser: Learning to Steer KV Cache for Efficient Localized Context Erasing

Mufei Li, Shikun Liu, Dongqi Fu +5

Post-hoc context erasing over the KV cache is challenging because a local edit has a global consequence: once a span has been processed, its influence propagates into the cached st…

cs.AI2026

Towards Direct Latent-Space Synthesis for Parallel Branches in LLM-Agent Workflows

Shikun Liu, Mufei Li, Dongqi Fu +5

Large language models increasingly serve as execution engines for agentic systems, yet they still consume context through a sequential text interface. This creates a mismatch with…

cs.IR2026

ChronoID: Infusing Explicit Temporal Signals into Semantic IDs for Generative Recommendation

Dongdong Nian, Dongqi Fu, Chenliang Xu +4

Semantic IDs are crucial in generative recommendation, but with a fundamental limitation: temporal information is not well incorporated into semantic IDs. Instead, time influences…