3 citations · 5 across the 26 of their papers we have counts for
5 papers · 1 filter
Calibrate the Decisions That Change the Future: On-Policy Post-Training Quantization for Multimodal Large Language Models
Wenxiao Fan, Jingling Fu, Lichen Ma +6
Post-training quantization (PTQ) lowers deployment cost for multimodal large language models, but calibration typically reconstructs fixed sequences with local objectives. This ove…
Is Reasoning Always Useful? Rethinking Reasoning Utility in Universal Multimodal Embeddings
Wenxiao Fan, Jingling Fu, Luohang Liu +6
Reasoning-enhanced universal multimodal embeddings (UME) improve heterogeneous retrieval, but plausible rationales do not necessarily produce discriminative rankings. We study this…
On Time, Within Budget: Constraint-Driven Online Resource Allocation for Agentic Workflows
Xinglin Wang, Zishen Liu, Shaoxiong Feng +9
Agentic systems increasingly solve complex user requests by executing orchestrated workflows, where subtasks are assigned to specialized models or tools and coordinated according t…
Learning More from Less: Unlocking Internal Representations for Benchmark Compression
Yueqi Zhang, Jin Hu, Shaoxiong Feng +9
The prohibitive cost of evaluating Large Language Models (LLMs) necessitates efficient alternatives to full-scale benchmarking. Prevalent approaches address this by identifying a s…
Mind the Quote: Enabling Quotation-Aware Dialogue in LLMs via Plug-and-Play Modules
Yueqi Zhang, Peiwen Yuan, Shaoxiong Feng +7
Human-AI conversation frequently relies on quoting earlier text-"check it with the formula I just highlighted"-yet today's large language models (LLMs) lack an explicit mechanism f…