AI Research

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My thoughts on Jev

I‘m sure you heard about Jev, but the information about it you could find was nothing but hype.

Stanford's Paper2Agent Turns Research Papers Into Working AI Agents

Stanford researchers built Paper2Agent, a system that transforms scientific papers from static PDFs into AI agents capable of running analyses, applying methods to new data and collaborating with other research agents.…

Break Your Own RAG Pipeline Before Users Do

A small adversarial test set that catches the retrieval failures your evaluation set never will The post Break Your Own RAG Pipeline Before Users Do appeared first on Towards Data Science.

Build a Speaker-Recognition App with Claude Code

Learn how to effectively code up an internal tool using Claude code or Codex The post Build a Speaker-Recognition App with Claude Code appeared first on Towards Data Science.

OpenClaw 2.0 Is Turning AI Agents Into a Multiplayer Workforce

OpenClaw chief architect Vincent Koc showed how the team is building with dozens of agents, shared sessions, remote compute, model routing, and persistent memory.

4 Ways to Use AI on a PhD Thesis

Finding citations, consolidating code, fact-checking and preparing for the defence The post 4 Ways to Use AI on a PhD Thesis appeared first on Towards Data Science.

An Introduction to Jev

The AI that makes decisions instead of generating text The post An Introduction to Jev appeared first on Towards Data Science.

😺 Amazon blocked Meta’s Muse from shopping

PACE: Precise AI Cinematic Expression

arXiv:2609.19853v2 Announce Type: replace-cross Abstract: Between a screenplay and a film sits a planning problem that is spatial first: who stands where, and what a camera sees from where it stands. An image diffusion…

Constraint Decay: The Fragility of LLM Agents in Backend Code Generation

arXiv:2605.06445v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) agents demonstrate strong performance in autonomous code generation under loose specifications. However, production-grade software…

Knowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering

arXiv:2609.18317v2 Announce Type: replace-cross Abstract: Large language models (LLMs) suffer from a long-tail deficit: culturally specific facts, particularly those concerning underrepresented regions such as Latin…

Co-Evolving Zero-Day Jamming: Adaptive Attack Synthesis and Graph Attention-Based Online Detection

arXiv:2609.21334v1 Announce Type: cross Abstract: Effective evaluation of zero-day jamming detectors requires robust adversarial models. However, existing attack models often assume prior knowledge of the target…

On Repulsive and Attractive Teachers: Separating Correctness from Behavior in Self-Distillation

arXiv:2609.21561v1 Announce Type: cross Abstract: On-policy self-distillation provides dense, token-level supervision by conditioning a model on privileged information and distilling the resulting teacher distribution…

Rethinking Multi-Agent Collaboration: When More Is Less

arXiv:2609.19759v2 Announce Type: replace Abstract: The rapid advancement of large language models and single-agent harnesses has reshaped the landscape of autonomous systems, raising a critical question of when…

Accelerating Dense LLMs via L0-regularized Mixture-of-Experts

arXiv:2609.21672v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance but suffer from slow and costly inference. Existing acceleration methods often lead to noticeable performance…

Decoupling Internal Representational Changes and Causal Importance in Fine-Tuned Large Language Models

arXiv:2609.21113v1 Announce Type: new Abstract: Fine-tuning has emerged as a widely adopted approach for adapting LLMs to a variety of downstream tasks. However, how it reshapes their internal mechanisms remains poorly…

Scaling Discovery through Test-Time Communication

arXiv:2609.21032v1 Announce Type: cross Abstract: Science advances not in isolation but through collaboration, yet existing agentic systems capture little of this. Whether communicating agents help remains an open…

A Lie Detector Test for Language Models: Reading Knowledge a Model Won't Reveal

arXiv:2609.21996v1 Announce Type: new Abstract: Large language models can hold knowledge they do not report. A model may sandbag on a capability evaluation, or answer against what it internally knows, and its outputs…

Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models

arXiv:2608.27259v1 Announce Type: cross Abstract: World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction. Recent WAMs increasingly perform such…