41 citations · 64 across the 26 of their papers we have counts for
22 papers · 1 filter
Capsule Lens: Locating and Tracking Concept Geometry in Model Representations
Yiming Tang, Harshvardhan Saini, Samyak Jha +3
Understanding how concepts are encoded in the internal representations of machine learning models is a central problem in mechanistic interpretability, essential both for the scien…
SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning
Quenton Yeo, Zhaoge Bi, Linghan Huang +3
Rapid earthquake magnitude estimation is central to earthquake early warning, yet many operational systems depend on dense regional seismic networks and region-specific calibration…
When Context Misleads: Intent-Guided Decoding for Robust Retrieval-Augmented Generation
Haolin Jin, Pengyue Yang, Huaming Chen
Retrieval-augmented generation (RAG) improves large language models by grounding generation in external evidence, but it also introduces a source trust problem: retrieved context m…
Characterizing Large Language Model Agentic Workflows: A Study on N8n Ecosystem
Yutian Tang, Yuming Zhou, Huaming Chen
Large Language Models (LLMs) are rapidly being adopted in low-code and no-code automation platforms, where non-expert users design workflows that combine natural language understan…
Position: Vision-Language-Action Models Cannot Be Verified to Perform Physical Reasoning
Taozhao Chen, Ian Manchester, Huaming Chen
Vision-Language-Action (VLA) systems, built on pretrained vision-language models (VLMs), have shown rapidly improving performance on robot manipulation benchmarks. These gains are…
Latent Action Reparameterization for Efficient Agent Inference
Wenhao Huang, Qingwen Zeng, Qiyue Chen +11
Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inference cost. While prior wor…
ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles
Yitian Yang, Yiqun Duan, Linghan Huang +4
Large language model (LLM)-based multi-agent simulation offers a powerful testbed for studying social opinion dynamics. Yet current approaches often adopt two contrasting methods:…
The 1/W Law: An Analytical Study of Context-Length Routing Topology and GPU Generation Gains for LLM Inference Energy Efficiency
Huamin Chen, Xunzhuo Liu, Yuhan Liu +3
How many tokens can a GPU inference cluster deliver per watt? Across deployments of identical hardware, the answer varies by 40x -- not because of software inefficiency, but becaus…
Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference
Huamin Chen, Xunzhuo Liu, Junchen Jiang +2
Production vLLM fleets provision every instance for worst-case context length, wasting 4-8x concurrency on the 80-95% of requests that are short and simultaneously triggering KV-ca…
Dual-Pool Token-Budget Routing for Cost-Efficient and Reliable LLM Serving
Xunzhuo Liu, Bowei He, Xue Liu +3
Production vLLM fleets typically provision each instance for the worst-case context length, leading to substantial KV-cache over-allocation and under-utilized concurrency. In pract…
The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
Huamin Chen, Xunzhuo Liu, Bowei He +5
Over the past year, the vLLM Semantic Router project has released a series of work spanning: (1) core routing mechanisms -- signal-driven routing, context-length pool routing, rout…
From Inference Routing to Agent Orchestration: Declarative Policy Compilation with Cross-Layer Verification
Huamin Chen, Xunzhuo Liu, Bowei He +1
The Semantic Router DSL is a non-Turing-complete policy language deployed in production for per-request LLM inference routing: content signals (embedding similarity, PII detection,…
Knowledge Access Beats Model Size: Memory Augmented Routing for Persistent AI Agents
Xunzhuo Liu, Bowei He, Xue Liu +3
Production AI agents frequently receive user-specific queries that are highly repetitive, with up to 47\% being semantically similar to prior interactions, yet each query is typica…
Conflict-Free Policy Languages for Probabilistic ML Predicates: A Framework and Case Study with the Semantic Router DSL
Xunzhuo Liu, Hao Wu, Huamin Chen +2
Conflict detection in policy languages is a solved problem -- as long as every rule condition is a crisp Boolean predicate. BDDs, SMT solvers, and NetKAT all exploit that assumptio…
FleetOpt: Analytical Fleet Provisioning for LLM Inference with Compress-and-Route as Implementation Mechanism
Huamin Chen, Xunzhuo Liu, Yuhan Liu +3
Modern LLM GPU fleets are provisioned for worst-case context lengths that the vast majority of requests never approach, wasting GPU capacity on idle KV-cache slots. We present Flee…
inference-fleet-sim: A Queueing-Theory-Grounded Fleet Capacity Planner for LLM Inference
Huamin Chen, Xunzhuo Liu, Yuhan Liu +3
Sizing a GPU fleet for LLM inference is harder than it looks. The obvious questions -- how many GPUs, which type, where to split a two-pool fleet -- have no closed-form answers. Th…
Visual Confused Deputy: Exploiting and Defending Perception Failures in Computer-Using Agents
Xunzhuo Liu, Bowei He, Xue Liu +3
Computer-using agents (CUAs) act directly on graphical user interfaces, yet their perception of the screen is often unreliable. Existing work largely treats these failures as perfo…
Outcome-Aware Tool Selection for Semantic Routers: Latency-Constrained Learning Without LLM Inference
Huamin Chen, Xunzhuo Liu, Junchen Jiang +2
Semantic routers in LLM inference gateways select tools in the critical request path, where every millisecond of added latency compounds across millions of requests. We propose Out…
Adaptive Vision-Language Model Routing for Computer Use Agents
Xunzhuo Liu, Bowei He, Xue Liu +3
Computer Use Agents (CUAs) translate natural-language instructions into Graphical User Interface (GUI) actions such as clicks, keystrokes, and scrolls by relying on a Vision-Langua…
98 Faster LLM Routing Without a Dedicated GPU: Flash Attention, Prompt Compression, and Near-Streaming for the vLLM Semantic Router
Xunzhuo Liu, Bowei He, Xue Liu +3
System-level routers that intercept LLM requests for safety classification, domain routing, and PII detection must be both fast and operationally lightweight: they should add minim…
Fast and Faithful: Real-Time Verification for Long-Document Retrieval-Augmented Generation Systems
Xunzhuo Liu, Bowei He, Xue Liu +2
Retrieval-augmented generation (RAG) is increasingly deployed in enterprise search and document-centric assistants, where responses must be grounded in long and complex source mate…
vLLM Semantic Router: Signal Driven Decision Routing for Mixture-of-Modality Models
Xunzhuo Liu, Huamin Chen, Samzong Lu +30
As large language models (LLMs) diversify across modalities, capabilities, and cost profiles, the problem of intelligent request routing: selecting the right model for each query a…