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AI Will Do Your Job. That Should Be Good News.

The case for paying people to play when machines do the work The post AI Will Do Your Job. That Should Be Good News. appeared first on Towards Data Science.

A Good Shooter or Just a Good Shot Selector? Using Python to Find Out

In basketball, field-goal percentage tells us how often a player makes a shot. But what about the shots’ difficulty? Let's use Python and machine learning to separate shot selection from shot making. The post A Good…

Your Agent Works in the Demo. Now Make It Survive Monday.

The demo is the easy part The post Your Agent Works in the Demo. Now Make It Survive Monday. appeared first on Towards Data Science.

Three Techniques to Understand Your Codebase When Coding Agents Write the Code

Learn how to use Claude Code to write feature memos, review pull requests, and build visual HTML explainers, so you understand what your agents ship The post Three Techniques to Understand Your Codebase When Coding…

😸 Proton’s AI staff revolt

AI Could Design Every Medicine, Says Isomorphic Labs. Human Trials Come Next

Isomorphic Labs predicts AI will eventually design every medicine, but its first drug candidates remain preclinical. IsoDDE has shown progress in molecular prediction; human testing lies ahead.

How Close Is Anthropic to AI That Can Improve Itself?

Anthropic warns AI could accelerate its own development. Its latest filing and independent research show what scientists can measure so far.

From Representation to Readout: Mechanistic Analysis of Membership Signals in Language Models

arXiv:2610.41445v1 Announce Type: cross Abstract: Membership inference aims to determine whether a particular example was included in a model's training data. Such membership signals are often broadly described as…

I3L: Iterative Interactive Imitation Learning for Whole-Body Mobile Manipulation

arXiv:2610.17748v2 Announce Type: replace-cross Abstract: Policies trained offline from teleoperated demonstrations can degrade outside their training distribution. This gap is particularly acute in long-horizon…

Beyond Public Access in LLM Pre-Training Data

arXiv:2505.00020v3 Announce Type: replace-cross Abstract: Using a legally obtained dataset of 34 copyrighted O'Reilly Media books (13,962 paragraphs), we apply the DE-COP membership inference attack to test whether…

Turing LLM Post-Training: Calibrated Distillation and Efficient Dynamic-MoE Execution

arXiv:2610.39876v2 Announce Type: replace-cross Abstract: We study post-training for dynamically routed mixture-of-experts (MoE) models, focusing on integrating independently optimized specialists while keeping…

Instruction-Tuning Open-Weight Language Models for BPMN Model Generation

arXiv:2512.12063v2 Announce Type: replace-cross Abstract: Domain models are central to software engineering, as they enable a shared understanding, guide implementation, and support automated analyses and model-driven…

Speech-DRAME: A Framework for Human-Aligned Benchmarks in Speech Role-Play

arXiv:2511.01261v2 Announce Type: replace-cross Abstract: Evaluating spoken role-play requires judging not only linguistic content but also prosody, emotional expression, character embodiment, and contextual fit.…

Optimizing Anytime Reasoning via Budget Relative Policy Optimization

arXiv:2505.13438v4 Announce Type: replace-cross Abstract: Scaling test-time compute is crucial for enhancing the reasoning capabilities of large language models (LLMs). Existing approaches typically employ reinforcement…

On the Faithfulness of Visual Thinking: Measurement and Enhancement

arXiv:2510.23482v2 Announce Type: replace-cross Abstract: Recent large vision-language models (LVLMs) can generate vision-text multimodal chain-of-thought (MCoT) traces after reinforcement fine-tuning (RFT). However, we…

Hierarchical Cooperative GFlowNets

arXiv:2610.33968v2 Announce Type: replace-cross Abstract: Generative Flow Networks (GFlowNets) are trained to sample objects from compositional spaces with probability proportional to a reward function, but ineffective…

CogBattery: Human-Referenced Evaluation of Cognitive Task Behavior and Structure in Language Models

arXiv:2607.24999v2 Announce Type: replace-cross Abstract: Human cognitive tasks let us compare language models with humans under controlled conditions. Yet a model can reproduce the direction of a human effect while…

Aligning MLLMs with the Latent Structure of Human Cognition via Behavior-Derived Semantic Dimensions

arXiv:2610.41951v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved impressive performance across a wide range of reasoning tasks, yet it remains unclear whether their internal…

A Unified Attack Framework against Statistical Generative Watermarks for Large Language Models

arXiv:2610.27653v2 Announce Type: replace-cross Abstract: Watermarking has emerged as a key tool for identifying text generated by large language models (LLMs), with current schemes embedding statistical signals into…

Reject, Remember, Retry: Why Multi-Turn Attackers Should Remember Their Mistakes

arXiv:2610.31937v2 Announce Type: replace Abstract: Existing multi-turn jailbreak attackers condition on the same conversation history as the target. We introduce $R^3$ (Reject, Remember, Retry), a black-box multi-LLM…