13 citations · 29 across the 37 of their papers we have counts for
38 papers
Cavity-tunable Pseudospin-Hall Topology and Edge Transport
Minghui Niu, Yan Meng, Chengle Fan +5
Topological edge states are a hallmark of topological phases, with their existence tied to bulk band topology through bulk-edge correspondence. In photonic pseudospin-Hall systems,…
Audio-Zero: Label-Free Self-Evolution for Fine-Grained Audio Reasoning
Siqian Tong, Xuan Li, Chaozhuo Li +5
Large Audio Language models (LALMs) have made rapid progress on acoustic understanding, yet they still struggle with fine-grained audio reasoning (e.g., recognizing event order, re…
Multimodal Reward Hacking in Reinforcement Learning
Jiayu Yao, Yiwei Wang, Anmeng Zhang +5
Reinforcement learning (RL) is increasingly used to align multimodal large language models (MLLMs), but higher rewards do not always imply better task performance. This risk is amp…
Lost in a Single Vector: Improving Long-Document Retrieval with Chunk Evidence Aggregation
Shanshan Lyu, Yiwei Wang, Yujun Cai +2
Dense retrieval ranks one query vector against one document vector. On long documents, this interface can fail when a short but decisive span is weakened during document encoding b…
Rethinking Synthetic Rationale Supervision for Disease Prediction
Buxin Su, Bingxuan Li, Cheng Qian +3
Supervised fine-tuning with synthetic rationales is widely assumed to improve clinical prediction by teaching models not only what to predict but why. We test this assumption on fi…
Readable Yet Unpredictable: Rotated-Outcome Prediction in Vision-Language Models
Lexin Wang, Shenghua Liu, Yiwei Wang +2
Can vision-language models predict what a 180° rotation would reveal from the original image alone? We study this ability through Rotated-Outcome Prediction: given an original imag…
Agentic AI and Human-in-the-Loop Interventions: Field Experimental Evidence from Alibaba's Customer Service Operations
Yiwei Wang, Chuan Zhu, Tianjun Feng +2
Agentic AI systems that autonomously perform service tasks are entering customer service operations. However, limited evidence exists on how human interventions shape service outco…
Head Forcing: Long Autoregressive Video Generation via Head Heterogeneity
Jiahao Tian, Yiwei Wang, Gang Yu +1
Autoregressive video diffusion models support real-time synthesis but suffer from error accumulation and context loss over long horizons. We discover that attention heads in AR vid…
TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning
Bowen Sun, Chaozhuo Li, Yaodong Yang +2
Decompositional jailbreaks pose a critical threat to large language models (LLMs) by allowing adversaries to fragment a malicious objective into a sequence of individually benign q…
How Creative Are Large Language Models in Generating Molecules?
Wen Tao, Yiwei Wang, Peng Zhou +6
Molecule generation requires satisfying multiple chemical and biological constraints while searching a large and structured chemical space. This makes it a non-binary problem, wher…
HighlightBench: Benchmarking Markup-Driven Table Reasoning in Scientific Documents
Lexin Wang, Shenghua Liu, Yiwei Wang +5
Visual markups such as highlights, underlines, and bold text are common in table-centric documents. Although multimodal large language models (MLLMs) have made substantial progress…
Harmonizing Dense and Sparse Signals in Multi-turn RL: Dual-Horizon Credit Assignment for Industrial Sales Agents
Haojin Yang, Ai Jian, Xinyue Huang +5
Optimizing large language models for industrial sales requires balancing long-term commercial objectives (e.g., conversion rate) with immediate linguistic constraints such as fluen…
Generative AI in Action: Field Experimental Evidence from Alibaba's Customer Service Operations
Xiao Ni, Yiwei Wang, Tianjun Feng +3
In collaboration with Alibaba, we study how a generative AI assistant affects service performance in e-commerce after-sales operations. In a large-scale field experiment, human age…
PRISM-: Differential Subspace Steering for Prompt Highlighting in Large Language Models
Yuyao Ge, Shenghua Liu, Yiwei Wang +5
Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing approaches is extracting steeri…
PromptCD: Test-Time Behavior Enhancement via Polarity-Prompt Contrastive Decoding
Baolong Bi, Yuyao Ge, Shenghua Liu +9
Reliable AI systems require large language models (LLMs) to exhibit behaviors aligned with human preferences and values. However, most existing alignment approaches operate at trai…
AuTAgent: A Reinforcement Learning Framework for Tool-Augmented Audio Reasoning
Siqian Tong, Xuan Li, Yiwei Wang +5
Large Audio Language Models (LALMs) excel at perception but struggle with complex reasoning requiring precise acoustic measurements. While external tools can extract fine-grained f…
Gated Differentiable Working Memory for Long-Context Language Modeling
Lingrui Mei, Shenghua Liu, Yiwei Wang +7
Long contexts challenge transformers: attention scores dilute across thousands of tokens, critical information is often lost in the middle, and models struggle to adapt to novel pa…
Reward and Guidance through Rubrics: Promoting Exploration to Improve Multi-Domain Reasoning
Baolong Bi, Shenghua Liu, Yiwei Wang +6
Recent advances in reinforcement learning (RL) have significantly improved the complex reasoning capabilities of large language models (LLMs). Despite these successes, existing met…
Not in Sync: Unveiling Temporal Bias in Audio Chat Models
Jiayu Yao, Shenghua Liu, Yiwei Wang +5
Large Audio Language Models (LALMs) are increasingly applied to audio understanding and multimodal reasoning, yet their ability to locate when events occur remains underexplored. W…
A Survey of Vibe Coding with Large Language Models
Yuyao Ge, Lingrui Mei, Zenghao Duan +12
The advancement of large language models (LLMs) has catalyzed a paradigm shift from code generation assistance to autonomous coding agents, enabling a novel development methodology…
Focusing by Contrastive Attention: Enhancing VLMs' Visual Reasoning
Yuyao Ge, Shenghua Liu, Yiwei Wang +6
Vision-Language Models (VLMs) have demonstrated remarkable success across diverse visual tasks, yet their performance degrades in complex visual environments. While existing enhanc…
A Survey of Context Engineering for Large Language Models
Lingrui Mei, Jiayu Yao, Yuyao Ge +12
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. This survey introduces Context Engineering, a f…
RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs
Baolong Bi, Shenghua Liu, Xingzhang Ren +7
The foundational capabilities of large language models (LLMs) are deeply influenced by the quality of their pre-training corpora. However, enhancing data quality at scale remains a…
Who is in the Spotlight: The Hidden Bias Undermining Multimodal Retrieval-Augmented Generation
Jiayu Yao, Shenghua Liu, Yiwei Wang +5
Multimodal Retrieval-Augmented Generation (RAG) systems have become essential in knowledge-intensive and open-domain tasks. As retrieval complexity increases, ensuring the robustne…