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keplerccc submitted a paper 6 days ago

GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks

Junyi42 submitted a paper 24 days ago

Playful Agentic Robot Learning

yuanbopang authored a paper about 1 month ago

Agents' Last Exam

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Papers

GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks

Playful Agentic Robot Learning

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Berkeley 's papers 22

Submitted by

Kaiyuan Eric Chen

GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks

Berkeley

Submitted by

Junyi Zhang

Playful Agentic Robot Learning

Berkeley

Submitted by

Han

Agents' Last Exam

Berkeley

Submitted by

Shangding Gu

From Model Scaling to System Scaling: Scaling the Harness in Agentic AI

Berkeley

Submitted by

Yunkai Zhang

Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models

Berkeley

Submitted by

Hanchen Li

Combee: Scaling Prompt Learning for Self-Improving Language Model Agents

Berkeley

Submitted by

Shreya Shankar

Can AI Agents Answer Your Data Questions? A Benchmark for Data Agents

Berkeley

Submitted by

Haocheng Xi

Flash-KMeans: Fast and Memory-Efficient Exact K-Means

Berkeley

Submitted by

Haocheng Xi

SVG-EAR: Parameter-Free Linear Compensation for Sparse Video Generation via Error-aware Routing

Berkeley

Offline Materials Optimization with CliqueFlowmer

Berkeley

Submitted by

Harman Singh

V_1: Unifying Generation and Self-Verification for Parallel Reasoners

Berkeley

Submitted by

Xuandong Zhao

Self-Sovereign Agent

Berkeley

Submitted by

Zhanhui Zhou

dLLM: Simple Diffusion Language Modeling

Berkeley

Submitted by

Jintao Zhang

SLA2: Sparse-Linear Attention with Learnable Routing and QAT

Berkeley

5

Submitted by

Xianyang Liu

AgenticPay: A Multi-Agent LLM Negotiation System for Buyer-Seller Transactions

Berkeley

Submitted by

Xuandong Zhao

InfoSynth: Information-Guided Benchmark Synthesis for LLMs

Berkeley

Submitted by

Chuyi Shang

Latent Implicit Visual Reasoning

Berkeley

5

Submitted by

Yongyuan Liang

MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Model for Embodied Task Planning

Berkeley

Submitted by

Roei Herzig

Learning to Grasp Anything by Playing with Random Toys

Berkeley

Submitted by

Zhixuan Liang

VER: Vision Expert Transformer for Robot Learning via Foundation Distillation and Dynamic Routing

Berkeley

Submitted by

Toby Kreiman

Transformers Discover Molecular Structure Without Graph Priors

Berkeley

The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains

Berkeley