10 papers
Forward Pass Domain Adaptation (Without Cross-Layer Backpropagation)
Rivaan Patil, Simon Dennis, Hao Guo +1
Forward-Pass-Only MLP training (FPO) adapts large language models without a backward pass through the model body, achieving 2.7--3.2x the throughput of standard fine-tuning at ~40%…
MMShopBench: A Real-Log Benchmark for Multimodal, Multi-Turn Shopping Agents
Zeying Hao, Hao Guo, Mengtao Xu +5
Online shoppers increasingly turn to AI shopping assistants, using images and multi-turn dialogue to express and refine product needs that are difficult to articulate in text alone…
Procedural Knowledge Is Not Low-Rank: Why LoRA Fails to Internalize Multi-Step Procedures
Simon Dennis, Kevin Shabahang, Hao Guo +1
Parameter-efficient fine-tuning methods like LoRA have become the default for adapting large language models, succeeding across instruction following, style transfer, and factual a…
SkillChain: Closing the Loop on Skill Evolution for Image-Based E-Commerce AI Assistants
Yimin Hu, Mengtao Xu, Hao Guo +3
Image-based AI assistants are now deployed at production scale on e-commerce platforms, where a single uploaded image can trigger fundamentally different user intents: product sear…
When Mean CE Fails: Median CE Can Better Track Language Model Quality
Hao Guo, Simon Dennis, Rivaan Patil +1
Mean cross-entropy is the standard validation metric for language models, but it can fail to track model quality during training. We examine this in two common scenarios. First, in…
Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction
Simon Dennis, Kevin Shabahang, Hao Guo +1
Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedly re-teach preferences, corr…
Compiling Agentic Workflows into LLM Weights: Near-Frontier Quality at Two Orders of Magnitude Less Cost
Simon Dennis, Rivaan Patil, Kevin Shabahang +1
Agent orchestration frameworks have proliferated, collectively exceeding 290,000 GitHub stars across LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, Semantic Kernel, Strands, and…
In-Context Prompting Obsoletes Agent Orchestration for Procedural Tasks
Simon Dennis, Michael Diamond, Rivaan Patil +2
Agent orchestration frameworks -- LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, and others -- place an external orchestrator above the LLM, tracking state and injecting routing…
Simulating Teams with LLM Agents: Interactive 2D Environments for Studying Human-AI Dynamics
Mohammed Almutairi, Charles Chiang, Haoze Guo +9
Enabling users to create their own simulations offers a powerful way to study team dynamics and performance. We introduce VirTLab, a system that allows researchers and practitioner…
VirtLab: An AI-Powered System for Flexible, Customizable, and Large-scale Team Simulations
Mohammed Almutairi, Charles Chiang, Haoze Guo +9
Simulating how team members collaborate within complex environments using Agentic AI is a promising approach to explore hypotheses grounded in social science theories and study tea…