arXiv:2609.40027v1 Announce Type: new Abstract: Causal action verifiers gate an agent’s state-changing tool calls by checking whether each proposed…
Prompt engineering fundamentals for Amazon Quick
Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the…
OSWorld-Science: A Benchmark of Computer Use Agents for Learning and Using Scientific Software
arXiv:2609.39903v1 Announce Type: new Abstract: Scientific software presents a demanding test for computer-using agents based on visual language models…
NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular Prediction
This post has no text preview — click the link below to read the original article. This article has been indexed from Hugging Face – Blog Read the original article: NVIDIA Kumo Tabular Sets a New Accuracy-Efficiency Frontier for Tabular…
From Messy Documents to Structured Data with Docling
Docling takes documents in whatever inconsistent format they arrive in, and converts them into one unified, structured representation that both people and…
ConflictGuide: AutoResearch Improves When Competing Behaviors Are Made Visible
arXiv:2609.39933v1 Announce Type: new Abstract: When designing machine learning models, desirable properties are often in tension: improving one behavior…
Prompt engineering by Quick component: Patterns and pitfalls
Part 2 of our Amazon Quick prompt engineering series goes component by component. Learn the prompt patterns that get the best results from Amazon Quick…
Better Deck or Different Judge? Evaluating Agentic Harness Gains in Corporate and Investment Banking
arXiv:2609.39958v1 Announce Type: new Abstract: Corporate and investment banking teams use presentations to support credit decisions and advise clients on…
Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock AgentCore
Manually extracting data from hundreds of vendor contracts doesn’t scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a…
Coverage Before Control: Route-Instruction Grounding and Steering for Controllable Retrosynthesis
arXiv:2609.39955v1 Announce Type: new Abstract: Single-step retrosynthesis models are commonly evaluated by their ability to recover recorded reactions.…
How Condé Nast built multimodal video discovery with Amazon Bedrock
Condé Nast’s editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions.…
GrammarRL: Effective Grammar-Constrained Decoding via Reinforcement Learning
arXiv:2609.39869v1 Announce Type: new Abstract: Grammar-constrained generation guarantees syntactic validity, but can substantially degrade semantic…
AI News Brief Hourly Summary 2026-10-01 18h : 19 posts
19 posts published in the last hour 15:34SuperWhisper s1-mini: The 600M Parameter Model Built Just for Transcription 15:34FIGS: Evaluating Multi-Turn Sycophancy Without Penalizing Empathy 15:33Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents 15:33OverForge: Reasoning Through…
SuperWhisper s1-mini: The 600M Parameter Model Built Just for Transcription
This is a summary of, and insights into, what I found digging into the recently-released Superwhisper S1 family of voice-to-text models.
FIGS: Evaluating Multi-Turn Sycophancy Without Penalizing Empathy
arXiv:2609.39863v1 Announce Type: new Abstract: Large language models frequently fail to balance staying truthful with being supportive. They often…
Getting the Source Right, Not Just the Fact: Source-Aware Verification for MCP Agents
This post has no text preview — click the link below to read the original article. This article has been indexed from Hugging Face – Blog Read the original article: Getting the Source Right, Not Just the Fact: Source-Aware Verification…
OverForge: Reasoning Through Strategies and Tactics Helps Cooperative Lifelong Adaptation
arXiv:2609.39727v1 Announce Type: new Abstract: Cooperative language-model agents must coordinate over long horizons and adapt to changing environments…
Brian Chesky interview: AI agents need their own operating system
Brian Chesky on making Airbnb agent-friendly, the state of consumer AI, and why the world needs an AI-native operating system.