Papers
Deep, long-form breakdowns of recent research in AI, machine learning, security & programming languages.
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RECAST: Learning to Compute the Right Context through Adaptive Evidence Routing
by Yilun Hao, Krishna Sayana, Isabella Ye, James S Ren, Sukhdeep Sodhi, Craig Boutilier, Chuchu Fan
Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models
by Daniel Robert Kling Alexander, Catherine Louise Kling
EmbodiedRSI: Active Continual Robot Learning Through Hypothesis-Guided Co-Evolution
by Python Song, Zhixuan Liang, Kelsey Fu, Mengdi Wang, Junfeng Yang, Shilong Liu
IdeaAnchor: Teaching LLMs to Turn Literature into Research Ideas
by Ziyu Chen, Yilun Zhao, Jiashuo Sun, Yiling Ma, Manasi Patwardhan, Arman Cohan
Sherpa: Teaching LLMs to Teach Adaptively
by Weixian Xu, Yanzhe Zhang, Zora Zhiruo Wang, Changyu Chen, Diyi Yang
Agent in a Bottle: Can LLM Agents Turn Their Capabilities Into Cheap, Scalable Artifacts?
by Ankit Sonthalia, Haritz Puerto, Alexander Rubinstein, Martin Gubri, Seong Joon Oh
AdvSim2Real : Training Web Agents Against Adaptive Prompt Injection in a Web World Model
by Sarim Hashmi, Mukul Ranjan, Kshitij Mishra, Mikhail Kuznetsov, Praneeth Vepakomma, Nils Lukas
The Missing Minimal Pair: Stereotype Evaluation in LLMs
by Nataliya Stepanova, Ivan Titov, Emily Allaway, Björn Ross
One Figure, Every Canvas: Editable Flowchart Relayout via Agentic Pipeline
by Shih-Chen Tseng, Chih-Hsuan Chen, Ryan Yang, Hsi-An Chen, Chun-Wei Tuan Mu, Yu-Lun Liu
TranScope: What the Software Hides About LLM Training Data, the Hardware Reveals at Scale, and Accelerators Magnify
by Joshua Kalyanapu, Darsh Asher, Kaushal Mhapsekar, Bita Aslrousta, Rushiraj Chaitanyakumar Sheth, Maharshi Mukeshkumar Oza, Achyuta Kannan, Samira Mirbagher Ajorpaz