1 citations · 1 across the 10 of their papers we have counts for
10 papers
Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing
Yutong Yin, Mingyu Jin, Jin Pan +12
Test-time scaling improves language-model reasoning, but existing approaches often face a difficult trade-off: long chain-of-thought sampling remains single-threaded, while sentenc…
Prefilling-dLLM: Predictive Prefilling for Long-Context Inference in Diffusion Language Models
Jing Xiong, Qi Han, Shansan Gong +6
Diffusion large language models (dLLMs) re-encode the entire prefix at every denoising step, causing recomputation that scales quadratically with context length and becomes prohibi…
CodeComp: Structural KV Cache Compression for Agentic Coding
Qiujiang Chen, Jing Xiong, Chenyang Zhao +2
Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value (KV) cache becomes the prim…
MMSpec: Benchmarking Speculative Decoding for Vision-Language Models
Hui Shen, Xin Wang, Ping Zhang +11
Vision-language models (VLMs) achieve strong performance on multimodal tasks but suffer from high inference latency due to large model sizes and long multimodal contexts. Speculati…
MMFormalizer: Multimodal Autoformalization in the Wild
Jing Xiong, Qi Han, Yunta Hsieh +11
Autoformalization, which translates natural language mathematics into formal statements to enable machine reasoning, faces fundamental challenges in the wild due to the multimodal…
ATTS: Asynchronous Test-Time Scaling via Conformal Prediction
Jing Xiong, Qiujiang Chen, Fanghua Ye +11
Large language models (LLMs) benefit from test-time scaling but are often hampered by high inference latency. Speculative decoding is a natural way to accelerate the scaling proces…
LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interaction
Weichu Liu, Jing Xiong, Yuxuan Hu +10
Large language models (LLMs) have made significant progress in Emotional Intelligence (EI) and long-context modeling. However, existing benchmarks often overlook the fact that emot…
SwingArena: Competitive Programming Arena for Long-context GitHub Issue Solving
Wendong Xu, Jing Xiong, Chenyang Zhao +16
We present SwingArena, a competitive evaluation framework for Large Language Models (LLMs) that closely mirrors real-world software development workflows. Unlike traditional static…
ParallelComp: Parallel Long-Context Compressor for Length Extrapolation
Jing Xiong, Jianghan Shen, Chuanyang Zheng +7
Extrapolating ultra-long contexts (text length >128K) remains a major challenge for large language models (LLMs), as most training-free extrapolation methods are not only severely…
CoPS: Empowering LLM Agents with Provable Cross-Task Experience Sharing
Chen Yang, Chenyang Zhao, Quanquan Gu +1
Sequential reasoning in agent systems has been significantly advanced by large language models (LLMs), yet existing approaches face limitations. Reflection-driven reasoning relies…