activity
20232026
most citedTowards Understanding the Capability of Large Language Models on Code Clone Detection: A Survey

9 citations · 11 across the 10 of their papers we have counts for

collaborators
Showing 2026Show all

8 papers · 1 filter

cond-mat.quant-gas2026

Analog Cosmology in a Quenched Bose-Einstein Condensate Bubble

Ruotong Zhai, Brendan Rhyno, Zain Mehdi +3

Recent interest and realization of ultracold bosons confined in shell-shaped, or bubble, traps have opened up several directions in the study of Bose-Einstein condensates (BECs) in…

cs.IR2026

Risk-Aware Reranking for Agentic Tool Retrieval

Qinfei Li, Xiaoxuan Dong, Jin Zhang +6

Tool retrieval determines which external tools are exposed to an LLM agent for a user query or task, making retrieval a critical pre-execution safety boundary. Unlike document retr…

cs.AI2026

Do We Really Need Multimodal Emotion Language Models Larger Than 1B Parameters?

Kaiwen Zheng, Junchen Fu, Wenhao Deng +3

Recent advances in multimodal large language models (MLLMs) have significantly improved the performance of multimodal emotion recognition (MER) and enabled interpretable descriptio…

cs.IR2026

RecRec: Latent Interests Recursive Reasoning for Sequential Recommendation

Wenhao Deng, Junchen Fu, Hanwen Du +6

Sequential recommender systems rely on a single forward pass to encode user interaction histories and predict the next item. Increasing inference-time computation through latent re…

cs.IR2026

Stream-aware Side Adaptation for Large Pre-trained Multimodal Embedding Models in Sequential Recommendation

Junchen Fu, Kaiwen Zheng, Ioannis Arapakis +4

Recently, large pretrained multimodal embedding models such as Qwen3-VL Embedding have shown strong promise for sequential recommendation, as they provide reusable semantic item re…

cs.AI2026

SkillAudit: From Fixed-Suite Benchmarking to Skill-Centered Assessment

Dexu Yu, Youhua Li, Zhaoyang Guan +12

Agent skills have become a practical way to extend large language model agents, but the growing skill ecosystem still lacks a reliable way to judge whether a skill is worth deployi…

cs.LG2026

RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data

Peiyan Hu, Haodong Feng, Hongyuan Liu +13

Predicting the evolution of complex physical systems remains a central problem in science and engineering. Despite rapid progress in scientific Machine Learning (ML) models, a crit…

cs.MM2026

Benchmarking Multimodal Large Language Models for Missing Modality Completion in Product Catalogues

Junchen Fu, Wenhao Deng, Kaiwen Zheng +5

Missing-modality information on e-commerce platforms, such as absent product images or textual descriptions, often arises from annotation errors or incomplete metadata, impairing b…