Meta-Learned Reward Shaping for Reinforcement Learning from Human Feedback
arXiv:2607.26094v1 Announce Type: new
Abstract: Reinforcement Learning from Human Feedback (RLHF) is the standard approach for aligning large language models with human preferences, but its quality is limited by static, task-agnostic reward models. This mismatch leads to sparse learning signals and...
Data Fusion and Contrastive Alignment for Unconstrained IR Molecular Structure Elucidation
arXiv:2607.26164v1 Announce Type: new
Abstract: Automated molecular structure elucidation from infrared (IR) spectroscopy data has seen significant advancements in recent years, but its broad applicability is limited by a reliance on pre-determined chemical formulas provided as auxiliary model inpu...
Shared SFT Lessons Across Alignment, Model Organisms, and Toy Models
arXiv:2607.26173v1 Announce Type: new
Abstract: Alignment training, model organisms, and toy models are usually treated as separate research areas. But projects in all three frequently use supervised fine-tuning (SFT) to pursue the same underlying goals. When projects share a goal, we should test w...
Even More Deception: Objective Misalignment in Mixed-Motive LLM Multi-Agent Systems
arXiv:2607.26120v1 Announce Type: new
Abstract: Large Language Models (LLMs)-powered multi-agent systems are increasingly deployed in mixed-motive environments, where agents operate under asymmetric information and strategic deception due to conflicting or hidden objectives. In these settings, misa...
ClinLens: Towards Long-Horizon Coding Agents for Longitudinal Multimodal Clinical Data Science
arXiv:2607.26155v1 Announce Type: new
Abstract: Clinical data-science agents must transform heterogeneous longitudinal records into auditable analyses, yet existing benchmarks largely isolate medical question answering, structured-table reasoning, or generic scientific repositories. We introduce CL...
Microsoft is openly competing with OpenAI, Anthropic more than ever
Microsoft pitched its own homegrown AI models, harnesses, and even a Mythos competitor on Wednesday, telling Wall Street it plans for continued growth.
MoMo: Dial Motion Mode in Robot Manipulation with Spatiotemporal Action Tokenization
To operate effectively across diverse contexts, robots must not only perform manipulation tasks accurately but also adapt how their actions unfold to the task, object, and interaction setting. We ask whether this execution-level variation can be learned as a reusable behavioral factor shared across ...
How avatarin built a 24/7 retail agent with GPT-Realtime
avatarin uses OpenAI’s GPT-Realtime to give Yamada Denki shoppers 24/7 multilingual support. In two weeks, 30,000 people used the agent and 92% of survey responses were positive.
Zuckerberg says Meta’s enterprise AI opportunity extends beyond agents
On the company’s second-quarter earnings call Wednesday, CEO Mark Zuckerberg said Meta sees a “large enterprise opportunity” spanning AI agents, APIs, compute, and internal software.
Discover what’s next for AI, from the SaaS reckoning to the agent security gap, at TechCrunch Disrupt 2026
At TechCrunch Disrupt 2026, the AI Stage is back to dig into the single hottest topic in the community for the past few years, presented by Google for Startups.
Prompt Engineering Is Solved—Prompt Management Isn’t
Prompt engineering helps you write better prompts—but it doesn’t help you change them safely. This article explores a common production failure where a simple variable rename breaks every live call, and introduces a lightweight static analysis tool that treats prompts like contracts, catching breaki...
Hint, a new AI startup co-founded by Martha Stewart, offers an AI assistant for homeowners
AI home management startup Hint, co-founded by Martha Stewart, wants to become an “AI for your home,” combining property records, maintenance schedules, home documents, and an AI assistant into a single app.
What Professionals Should Know About Data Science and AI, According to Harvard Business School Online
Learn why clear business goals, data quality, simple models, careful validation, realistic costs, and human judgment matter more than chasing the latest technology.
How a medical database developed at MIT evolved into a global standard of data-sharing
The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence.
Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search
Building an ALNS heuristic in Python for vehicle routing, time windows, capacity constraints, and mandatory driver breaks.
The post Los Movimientos, Part II: Solving Large Pickup-and-Delivery Problems with Adaptive Large Neighborhood Search appeared first on Towards Data Science.
Avoiding Entity Key Drift in a Data Lake: Step 1, Normalization
This is the opening piece of a four-part deep dive series, on building a high-frequency streaming pipeline against a live public API. The data source is openSenseMap, a citizen-science IoT network used for climate research, mostly in Germany. A live public API is what makes it useful: it produces da...
As AI content floods the internet, Pangram raises $9M to detect it
Pangram has raised $9 million to scale its AI detection software. The startup has also released a new AI text detection model, Pangram 4, and an AI image detection model in research preview.
The following article originally appeared on LinkedIn and is being republished here with the author’s permission. We’re currently at the peak of the hype cycle. On June 7, Peter Steinberger posted that you shouldn’t be prompting coding agents anymore; you should be designing loops that prompt your a...