29 citations · 35 across the 36 of their papers we have counts for
11 papers · 1 filter
SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching
Zhendong Mi, Pu Zhao, Ziyu Hu +4
Diffusion-based world models enable high-quality interactive environment generation but suffer from substantial inference overhead due to repeated Transformer evaluations during de…
Benchmarking Hybrid Deep Research Across Database Querying and Web Search
Ruofan Wu, Peiran Xu, Xiaolong Li +9
While autonomous agents have made significant strides in "deep research" by iteratively navigating the open web to synthesize information, real-world problem-solving is rarely conf…
An Executable Benchmarking Suite for Tool-Using Agents
Zhiqing Zhong, Zhijing Ye, Jiamin Wang +1
Closed-loop tool-using agents are increasingly evaluated in executable web, code, and micro-task environments, but benchmark reports often conflate workloads, action-generating dri…
KV-RM: Regularizing KV-Cache Movement for Static-Graph LLM Serving
Zhiqing Zhong, Zhijing Ye, Jian Zhang +3
Static-graph LLM decoders provide predictable launches, fixed tensor shapes, and low submission overhead, but online decoding exposes highly irregular KV-cache behavior: request le…
TLRD: Teaching LLMs to Reason over Tabular Data with Tri-Level Rationale Distillation
Tianyuan Liang, Xuwei Tan, Lei Shi +6
Tabular data is a primary medium for storing real-world information, driving many industrial applications of machine learning. Traditional predictors achieve strong predictive perf…
Residual Skill Optimization for Text-to-SQL Ensembles
Jiongli Zhu, Haoquan Guan, Parjanya Prajakta Prashant +8
Text-to-SQL ensembles improve over single-candidate generation by drawing multiple SQL candidates and selecting one, but their effectiveness is bounded by Pass@K, the probability t…
NCCLZ: Compression-Enabled GPU Collectives with Decoupled Quantization and Entropy Coding
Jiamin Wang, Zhijing Ye, Xiaodong Yu
Collective communication is a major bottleneck for multi-node GPU workloads in scientific computing and distributed deep learning, especially when inter-node bandwidth is limited.…
VideoSeek: Long-Horizon Video Agent with Tool-Guided Seeking
Jingyang Lin, Jialian Wu, Jiang Liu +6
Video agentic models have advanced challenging video-language tasks. However, most agentic approaches still heavily rely on greedy parsing over densely sampled video frames, result…
Effective MoE-based LLM Compression by Exploiting Heterogeneous Inter-Group Experts Routing Frequency and Information Density
Zhendong Mi, Yixiao Chen, Pu Zhao +4
Mixture-of-Experts (MoE) based Large Language Models (LLMs) have achieved superior performance, yet the massive memory overhead caused by storing multiple expert networks severely…
Reliable Use of Lemmas via Eligibility Reasoning and SectionAware Reinforcement Learning
Zhikun Xu, Xiaodong Yu, Ben Zhou +6
Recent large language models (LLMs) perform strongly on mathematical benchmarks yet often misapply lemmas, importing conclusions without validating assumptions. We formalize lemma$…
CD4LM: Consistency Distillation and aDaptive Decoding for Diffusion Language Models
Yihao Liang, Ze Wang, Hao Chen +7
Autoregressive large language models achieve strong results on many benchmarks, but decoding remains fundamentally latency-limited by sequential dependence on previously generated…