collaborators

8 papers

cs.SE2026

Structure-Aware Semantic Chunking with Title-Chain Prefixes: A 1600-Query Evaluation and the Measurement Trap in Text-Transform Ablations

Yang Yang

Chunking is the first and most consequential step in retrieval-augmented generation (RAG): every downstream retrieval decision inherits the chunk boundaries. We present a three-sta…

cs.AI2026

SubtleMemory: A Benchmark for Fine-Grained Relational Memory Discrimination in Long-Horizon AI Agents

Wenxuan Wang, Haoyu Sun, Fukuan Hou +4

Persistent AI assistants, such as OpenClaw, accumulate large collections of related memories over long-term interactions. As these memories grow, they may reinforce one another, di…

cs.CL2026

Agent Planning Benchmark: A Diagnostic Framework for Planning Capabilities in LLM Agents

Haoyu Sun, Wenxuan Wang, Mingyang Song +5

Planning is central to LLM agents: before acting, an agent must decompose goals, select tools, reason over constraints, and decide when a task is infeasible. Yet existing agent eva…

cs.AI2026

MAPGD: Multi-Agent Prompt Gradient Descent for Collaborative Prompt Optimization

Yichen Han, Yuhang Han, Siteng Huang +7

Prompt engineering is crucial for fully leveraging large language models (LLMs), yet most existing optimization methods follow a single trajectory, resulting in limited adaptabilit…

cs.DB2025

THOR: Transformer Heuristics for On-Demand Retrieval

Isaac Shi, Zeyuan Li, Fan Liu +4

We introduce the THOR (Transformer Heuristics for On-Demand Retrieval) Module, designed and implemented by eSapiens, a secure, scalable engine that transforms natural-language ques…

cs.CL2025

eSapiens's DEREK Module: Deep Extraction & Reasoning Engine for Knowledge with LLMs

Isaac Shi, Zeyuan Li, Fan Liu +4

We present the DEREK (Deep Extraction & Reasoning Engine for Knowledge) Module, a secure and scalable Retrieval-Augmented Generation pipeline designed specifically for enterprise d…