10 citations · 17 across the 35 of their papers we have counts for
38 papers
Grid-Bench: Can LLMs Predict How Discrete Worlds Change?
Zixiang Xu, Zirui Song, Wanrong Zheng +16
Spatial instructions describe how to move objects, transform regions, or modify their surroundings. When several operations are applied in sequence, each acts on a configuration sh…
LITERARYBIGFIVE: Author-Personalized Text Generation in a Unified Interpretable Space
Jinghui Zhang, Lang Gao, Ao Li +5
Personalized text generation for authors and literary writing is essential for applications such as adaptive writing assistants, creative support tools, and computational literary…
Measure, Don't Optimize: Forecasting Recovery in LLM Unlearning
Zirui Song, Huaxing Liu, Xiang Wang +8
Prior white-box studies show that large language models can retain latent traces of target knowledge after unlearning, even when the knowledge is no longer expressed in their outpu…
OmniFood-Bench: Evaluating VLMs for Nutrient Reasoning and Personalized Health Advice
Qian Jiang, Zhecheng Shi, Jingpu Yang +2
The rapid integration of Large Vision-Language Models (VLMs) into critical infrastructure promises to revolutionize personalized healthcare and dietary management. However, in the…
Inside the Unfair Judge: A Mechanistic Interpretability Account of LLM-as-Judge Bias
Zixiang Xu, Sixian Li, Huaxing Liu +4
Existing studies of LLM-as-judge scoring bias work predominantly at the input-output level: they perturb inputs, measure score deltas, and propose prompt-level mitigations. We argu…
Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory
Fengxian Ji, Zhuohan Xie, Jingpu Yang +3
With the rise of parametric memory, LoRA-based External Parametric Memory (EPM) has emerged as a modular solution, but existing routing methods often introduce additional training,…
Text-Driven 3D Indoor Scene Synthesis in Non-Manhattan Environments
Xianhui Meng, Zirui Song, Yuchen Zhang +10
Large Language Models (LLMs) have demonstrated remarkable capabilities in 3D indoor synthesis for Manhattan environments. However, existing methods often fail to capture plausible…
The Cylindrical Representation Hypothesis for Language Model Steering
Lang Gao, Jinghui Zhang, Wei Liu +7
Steering is a widely used technique for controlling large language models, yet its effects are often unstable and hard to predict. Existing theoretical accounts are largely based o…
Planning Takes More Than Token Prediction: Causal Plan for Benchmarking and Building Physically Grounded Embodied Reasoners
Zirong Song, Zheng Lu, Mingqi Gao +11
Current benchmarks for embodied vision-language planning inadvertently favor linguistic next-token prediction over physically grounded next-state reasoning. This rewards models tha…
MULTITEXTEDIT: Benchmarking Cross-Lingual Degradation in Text-in-Image Editing
Liwei Cheng, Shibo Feng, Lunjie Zhou +2
Text-in-image editing has become a key capability for visual content creation, yet existing benchmarks remain overwhelmingly English-centric and often conflate visual plausibility…
TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards
Mingxuan Cui, Jingpu Yang, Fengxian Ji +7
Faithful text rendering remains a persistent weakness of large text-to-image generative models, as it requires both semantic instruction following and fine-grained glyph-level stru…
FineState-Bench: Benchmarking State-Conditioned Grounding for Fine-grained GUI State Setting
Fengxian Ji, Jingpu Yang, Zirui Song +5
Despite the rapid progress of large vision-language models (LVLMs), fine-grained, state-conditioned GUI interaction remains challenging. Current evaluations offer limited coverage,…
Temporal Contrastive Decoding: A Training-Free Method for Large Audio-Language Models
Yanda Li, Yuhan Liu, Zirui Song +3
Large audio-language models (LALMs) generalize across speech, sound, and music, but unified decoders can exhibit a \emph{temporal smoothing bias}: transient acoustic cues may be un…
ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services
Fengxian Ji, Jingpu Yang, Zirui Song +5
Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. However, their performance on paid, real-wor…
FlashSign: Pose-Free Guidance for Efficient Sign Language Video Generation
Liuzhou Zhang, Zeyu Zhang, Biao Wu +10
Sign language plays a crucial role in bridging communication gaps between the deaf and hard-of-hearing communities. However, existing sign language video generation models often re…
Beyond Survival: Evaluating LLMs in Social Deduction Games with Human-Aligned Strategies
Zirui Song, Yuan Huang, Junchang Liu +7
Social deduction games like Werewolf combine language, reasoning, and strategy, providing a testbed for studying natural language and social intelligence. However, most studies red…
Do LLMs "Feel"? Emotion Circuits Discovery and Control
Chenxi Wang, Yixuan Zhang, Ruiji Yu +8
As the demand for emotional intelligence in large language models (LLMs) grows, a key challenge lies in understanding the internal mechanisms that give rise to emotional expression…
When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection
Lang Gao, Xuhui Li, Chenxi Wang +7
Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this ability also heightens the risk of…
DyFlow: Dynamic Workflow Framework for Agentic Reasoning
Yanbo Wang, Zixiang Xu, Yue Huang +9
Agent systems based on large language models (LLMs) have shown great potential in complex reasoning tasks, but building efficient and generalizable workflows remains a major challe…
FineState-Bench: A Comprehensive Benchmark for Fine-Grained State Control in GUI Agents
Fengxian Ji, Jingpu Yang, Zirui Song +6
With the rapid advancement of generative artificial intelligence technology, Graphical User Interface (GUI) agents have demonstrated tremendous potential for autonomously managing…
Under the Shadow of Babel: How Language Shapes Reasoning in LLMs
Chenxi Wang, Yixuan Zhang, Lang Gao +4
Language is not only a tool for communication but also a medium for human cognition and reasoning. If, as linguistic relativity suggests, the structure of language shapes cognitive…
Divide-Fuse-Conquer: Eliciting "Aha Moments" in Multi-Scenario Games
Xiaoqing Zhang, Huabin Zheng, Ang Lv +5
Large language models (LLMs) have been observed to suddenly exhibit advanced reasoning abilities during reinforcement learning (RL), resembling an ``aha moment'' triggered by simpl…
ManipLVM-R1: Reinforcement Learning for Reasoning in Embodied Manipulation with Large Vision-Language Models
Zirui Song, Guangxian Ouyang, Mingzhe Li +10
Large Vision-Language Models (LVLMs) have recently advanced robotic manipulation by leveraging vision for scene perception and language for instruction following. However, existing…
Evaluate Bias without Manual Test Sets: A Concept Representation Perspective for LLMs
Lang Gao, Kaiyang Wan, Wei Liu +6
Bias in Large Language Models (LLMs) significantly undermines their reliability and fairness. We focus on a common form of bias: when two reference concepts in the model's concept…