2 citations · 6 across the 38 of their papers we have counts for
43 papers
SkillNEO: Non-Elitist Evolutionary Optimization of Agent Skills
Enze Ma, Chunyu Miao, Yankai Chen +14
Agent skills turn procedural knowledge into reusable artifacts, allowing LLM agents to accumulate and refine expertise through experience. Building on this, skill evolution iterati…
How Data Scales in Agentic Reinforcement Learning: Laws and Synthesis Strategies
Bowei He, Yankai Chen, Xiaokun Zhang +4
Pretraining scaling laws treat training data as a one-dimensional quantity: a token count. Agentic reinforcement learning (RL) inherits this scalar abstraction, but modern synthesi…
Discrete Diffusion Models: A Unified Framework from Tokenization to Generation
Ye Yuan, Weien Li, Rui Song +20
Discrete denoising diffusion models (DDMs) have recently emerged as a compelling alternative to autoregressive (AR) modeling for discrete data, offering parallel generation and ite…
Online Test-Time Adaptation for Generalizable Dynamic Graph Anomaly Detection
Jialun Zheng, Hanchen Yang, Jiannong Cao +3
Generalizable dynamic graph anomaly detection (DGAD) enables pretrained detectors to identify anomalies in unseen target domains without costly retraining. However, existing method…
Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents
Wei-Chieh Huang, Weizhi Zhang, Yuchen Wu +12
Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely the underlying medium in which…
ShiJianBench: From Dialogue to Decision for Long-Horizon Evaluation of Investment Advisors
Jie Gong, Maowei Jiang, Zhiwei Liu +14
Conversational investment advisors influence not only what users know, but also how they make subsequent decisions as market conditions evolve. Existing evaluations primarily asses…
AdaMTP: An Adaptive Training Paradigm for Multi-Token Prediction
Ziqiang Cui, Han Shi, Bowei He +8
Multi-Token Prediction (MTP) has emerged as an effective paradigm that augments a shared Large Language Model backbone with auxiliary heads, training the model to predict several f…
Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering
Zhuohan Xie, Xueqing Peng, Georgi Georgiev +18
FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence. Each final-test item pairs an English question with financial statements and n…
Overview of FinMMEval 2026 Task 1: Multilingual Financial Multiple-Choice Question Answering
Zhuohan Xie, Yuyang Dai, Rania Elbadry +18
FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi. The task tests whether systems can select the corr…
Branching Policy Optimization: Sandbox-Native Language Agent Reinforcement Learning
Bowei He, Yankai Chen, Xiaokun Zhang +1
Reinforcement learning has emerged as the dominant paradigm for training large language model (LLM) agents that interact with executable sandboxes. State-of-the-art algorithms such…
HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation
Yaozu Wu, Wei-Chieh Huang, Jizhou Guo +11
Large language models increasingly operate in settings where humans are active collaborators rather than passive task providers. We introduce HAS-Framework, a graph-based framework…
FinPersona-Bench: A Benchmark for Longitudinal Psychometric Stability of Autonomous Financial Agents
Muhammad Usman Safder, Ayesha Gull, Rania Elbadry +7
Large Language Models (LLMs) are increasingly deployed as autonomous financial agents initialized with explicit behavioral mandates such as "preserve capital" or "avoid speculative…
Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
Yankai Chen, Hanrong Zhang, Bowei He +2
Standard Set Representation Learning methods typically excel on curated data but often overlook the challenge of inference-time element corruption. This refers to scenarios where d…
FinReporting: An Agentic Workflow for Localized Reporting of Cross-Jurisdiction Financial Disclosures
Fan Zhang, Mingzi Song, Rania Elbadry +20
Financial reporting systems increasingly leverage Large Language Models (LLMs) to extract and summarize corporate disclosures. However, most existing approaches assume a single-mar…
GAM: Hierarchical Graph-based Agentic Memory for LLM Agents
Zhaofen Wu, Hanrong Zhang, Fulin Lin +9
To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining prior knowledge. Current uni…
Beyond Message Passing: A Semantic View of Agent Communication Protocols
Dun Yuan, Fuyuan Lyu, Ye Yuan +11
Agent communication protocols are becoming critical infrastructure for large language model (LLM) systems that must use tools, coordinate with other agents, and operate across hete…
The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
Huamin Chen, Xunzhuo Liu, Bowei He +5
Over the past year, the vLLM Semantic Router project has released a series of work spanning: (1) core routing mechanisms -- signal-driven routing, context-length pool routing, rout…
CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification
Hanrong Zhang, Shicheng Fan, Henry Peng Zou +11
Anthropic proposes the concept of skills for LLM agents to tackle multi-step professional tasks that simple tool invocations cannot address. A tool is a single, self-contained func…
When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
Henry Peng Zou, Chunyu Miao, Wei-Chieh Huang +16
As LLM agents transition from short, static problem solving to executing complex, long-horizon tasks in dynamic environments, the ability to handle user interruptions, such as addi…
Locally Confident, Globally Stuck: The Quality-Exploration Dilemma in Diffusion Language Models
Liancheng Fang, Aiwei Liu, Henry Peng Zou +7
Diffusion large language models (dLLMs) theoretically permit token decoding in arbitrary order, a flexibility that could enable richer exploration of reasoning paths than autoregre…
Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment
Yi Han, Yan Wang, Lingfei Qian +12
Large language model (LLM) agents are increasingly tested on complex tasks, but their ability to allocate scarce resources over long horizons remains unclear. Unlike reactive tasks…
Pedagogically-Inspired Data Synthesis for Language Model Knowledge Distillation
Bowei He, Yankai Chen, Xiaokun Zhang +4
Knowledge distillation from Large Language Models (LLMs) to smaller models has emerged as a critical technique for deploying efficient AI systems. However, current methods for dist…
Conv-FinRe: A Conversational and Longitudinal Benchmark for Utility-Grounded Financial Recommendation
Yan Wang, Yi Han, Lingfei Qian +11
Most recommendation benchmarks evaluate how well a model imitates user behavior. In financial advisory, however, observed actions can be noisy or short-sighted under market volatil…
A Survey of Agent Memory in the Second Half: Towards Self-Evolving and Long-Horizon Agents
Wei-Chieh Huang, Weizhi Zhang, Yueqing Liang +56
Research in artificial intelligence is shifting from model innovations and benchmark scores towards problem definition and rigorous real-world evaluation. As the field enters the "…