activity
20232026
most citedTime Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities

3 citations · 11 across the 17 of their papers we have counts for

collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2026

MemFold: Learning Compact Soft Memory for Long-Context Personalization via On-Policy Optimization

Jingxuan Wu, Yuzhe Yang, Yiqiao Huang +6

An assistant that serves the same user over a long horizon has to answer from what that user has revealed: which preferences still hold, which were revised, and which constraints a…

cs.CL2026

Auditing Agent Harness Safety

Chengzhi Liu, Yichen Guo, Yepeng Liu +8

LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. However, a harness can return a c…

cs.CL2026

Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling

Zhen Zhang, Changyi Yang, Zijie Xia +11

Tokens are the fundamental units of computation in modern autoregressive models, and generation length directly influences both inference cost and reasoning performance. Despite it…

cs.CL2025

MMRC: A Large-Scale Benchmark for Understanding Multimodal Large Language Model in Real-World Conversation

Haochen Xue, Feilong Tang, Ming Hu +13

Recent multimodal large language models (MLLMs) have demonstrated significant potential in open-ended conversation, generating more accurate and personalized responses. However, th…

cs.CL2024★ 3 cited

Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities

Hua Tang, Chong Zhang, Mingyu Jin +5

Large language models (LLMs) have been applied in many fields and have developed rapidly in recent years. As a classic machine learning task, time series forecasting has recently b…