4 days ago
Using thousands of AI agents to uncover new leads in biological data
See how OpenAI, PerturbAI, and Scripps Research used distributed AI agents to uncover promising research leads in data from millions of brain cells.
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4 days ago
Google Cloud Ships llm-d 1.0 With Cache-Aware Routing for TPU and GPU Fleets
Google, Red Hat and IBM released llm-d 1.0, an open-source Kubernetes-native stack for distributed LLM inference. It adds multi-tenant flow control, zero-downtime upgrades and agent-aware routing across vLLM, SGLang, TPUs and GPUs. The post…
4 days ago
Learning Transferable Latent User Preferences for Human-Aligned Decision Making
arXiv:2605.12682v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as reasoning modules in many applications, yet they often struggle to produce human-aligned decisions. Human-aligned decision-making requires accounting for both explicitly stated…
4 days ago
SPEM: Structure-Aware Procedural Memory for Efficient Skill Use in LLM Agents
arXiv:2610.26995v1 Announce Type: new Abstract: LLM-based agents increasingly rely on reusable skills. However, scaling skill libraries makes efficient and accurate skill use difficult. Full skill loading incurs high token and runtime overhead. In contrast,…
4 days ago
Model- and Layer-Level Closed-Loop Forecasting with SSM-Based Spiking Neural Networks
arXiv:2610.28495v1 Announce Type: cross Abstract: Deep State-Space Models (Deep SSMs) have shown promising performance and computational benefits in processing of time-series data with complex temporal dependencies. Spiking neural networks (SNNs) constitute a biologically inspired…
4 days ago
When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability
arXiv:2610.26964v1 Announce Type: new Abstract: Large language models (LLMs) struggle with classical planning, but benchmarks rarely distinguish structural difficulty from the difficulty of interpreting symbolic vocabulary. We examine seven STRIPS domains with BFS-optimal plan…
4 days ago
Adaptive Pullback: Reweighting Supervision at Penalty Jumps in On-Policy Distillation
arXiv:2610.28194v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises student-generated responses using sampled-token student-teacher log-ratios. A positive log-ratio penalizes a token that the student assigns higher probability to than the teacher, but its current…
4 days ago
LightCRS: Lightweight Multi-Domain Conversational Recommendation System
arXiv:2610.26948v1 Announce Type: new Abstract: Conversational recommender systems have recently adopted vision-language models to match user dialogue intents with multimodal product information. However, extending these methods to many product domains faces a dilemma: deploying…
4 days ago
Slots Are Not Speakers: Training-Free Speaker Linking for Frozen Streaming Diarizers
arXiv:2610.28053v1 Announce Type: cross Abstract: This paper presents a causal, training-free linker that allows a frozen streaming diarizer to track more speakers than it has output slots. Streaming end-to-end diarizers such as Streaming Sortformer…
4 days ago
Pareto-Optimal RTL Code Generation via Multi-Objective Reinforcement Learning with Large Language Models
arXiv:2610.26904v1 Announce Type: new Abstract: Recent studies have proposed reinforcement learning with verifiable rewards (RLVR) methods that enable LLMs to generate high-quality RTL circuits from natural-language specifications. Existing approaches optimize circuit PPA (Power, Performance,…
4 days ago
MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring
arXiv:2610.26913v1 Announce Type: new Abstract: The adoption of Large Language Models for radiology report structuring has been largely dominated by either proprietary cloud-based models or large open models requiring high-end GPUs for deployment, which…
4 days ago
DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution
arXiv:2610.26924v1 Announce Type: new Abstract: General-purpose agents are increasingly expected to perform professional analytics work, which requires sustained reasoning, iterative investigation, and reliable evidence. Training these capabilities requires diverse and challenging tasks. However, generating…