Reducing Text Bias in Synthetically Generated MCQAs for VLMs in Autonomous Driving
arXiv:2602.17677v1 Announce Type: new
Abstract: Multiple Choice Question Answering (MCQA) benchmarks are an established standard for measuring Vision Language Model (VLM) performance in driving tasks. However, we observe the known phenomenon that synthetically generated MCQAs are highly susceptible...
Joint Parameter and State-Space Bayesian Optimization: Using Process Expertise to Accelerate Manufacturing Optimization
arXiv:2602.17679v1 Announce Type: new
Abstract: Bayesian optimization (BO) is a powerful method for optimizing black-box manufacturing processes, but its performance is often limited when dealing with high-dimensional multi-stage systems, where we can observe intermediate outputs. Standard BO model...
BioBridge: Bridging Proteins and Language for Enhanced Biological Reasoning with LLMs
arXiv:2602.17680v1 Announce Type: new
Abstract: Existing Protein Language Models (PLMs) often suffer from limited adaptability to multiple tasks and exhibit poor generalization across diverse biological contexts. In contrast, general-purpose Large Language Models (LLMs) lack the capability to inter...
LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs
arXiv:2602.17681v1 Announce Type: new
Abstract: Post-training quantization (PTQ) is a widely used approach for reducing the memory and compute costs of large language models (LLMs). Recent studies have shown that applying invertible transformations to activations can significantly improve quantizat...
Duality Models: An Embarrassingly Simple One-step Generation Paradigm
arXiv:2602.17682v1 Announce Type: new
Abstract: Consistency-based generative models like Shortcut and MeanFlow achieve impressive results via a target-aware design for solving the Probability Flow ODE (PF-ODE). Typically, such methods introduce a target time $r$ alongside the current time $t$ to mo...
Epistemic Traps: Rational Misalignment Driven by Model Misspecification
arXiv:2602.17676v1 Announce Type: new
Abstract: The rapid deployment of Large Language Models and AI agents across critical societal and technical domains is hindered by persistent behavioral pathologies including sycophancy, hallucination, and strategic deception that resist mitigation via reinfor...
The Token Games: Evaluating Language Model Reasoning with Puzzle Duels
arXiv:2602.17831v1 Announce Type: new
Abstract: Evaluating the reasoning capabilities of Large Language Models is increasingly challenging as models improve. Human curation of hard questions is highly expensive, especially in recent benchmarks using PhD-level domain knowledge to challenge the most ...
El Agente Gr\'afico: Structured Execution Graphs for Scientific Agents
arXiv:2602.17902v1 Announce Type: new
Abstract: Large language models (LLMs) are increasingly used to automate scientific workflows, yet their integration with heterogeneous computational tools remains ad hoc and fragile. Current agentic approaches often rely on unstructured text to manage context ...
Alignment in Time: Peak-Aware Orchestration for Long-Horizon Agentic Systems
arXiv:2602.17910v1 Announce Type: new
Abstract: Traditional AI alignment primarily focuses on individual model outputs; however, autonomous agents in long-horizon workflows require sustained reliability across entire interaction trajectories. We introduce APEMO (Affect-aware Peak-End Modulation for...
VectifyAI Launches Mafin 2.5 and PageIndex: Achieving 98.7% Financial RAG Accuracy with a New Open-Source Vectorless Tree Indexing.
Building a Retrieval-Augmented Generation (RAG) pipeline is easy; building one that doesn’t hallucinate during a 10-K audit is nearly impossible. For devs in the financial sector, the ‘standard’ vector-based RAG approach—chunking text and hoping for the best—often results in a ‘text soup’ that loses...
The growing size of Large Language Models (LLMs) makes efficient inference challenging, primarily due to the memory demands of the autoregressive Key-Value (KV) cache. Existing eviction or compression methods reduce cost but rely on heuristics, such as recency or past attention scores, which serve o...
Prompt Repetition: The Overlooked Hack for Better LLM Results
Have you ever asked an LLM a question, changed the wording a few times, and still felt the answer wasn’t quite right? If you’ve worked with tools like ChatGPT or Gemini, you’ve probably rewritten prompts, added more context, or used phrases like “be concise” or “think step by step” to improve result...
Forget Keyword Imitation: ByteDance AI Maps Molecular Bonds in AI Reasoning to Stabilize Long Chain-of-Thought Performance and Reinforcement Learning (RL) Training
ByteDance Seed recently dropped a research that might change how we build reasoning AI. For years, devs and AI researchers have struggled to ‘cold-start’ Large Language Models (LLMs) into Long Chain-of-Thought (Long CoT) models. Most models lose their way or fail to transfer patterns during multi-st...
The Reality of Vibe Coding: AI Agents and the Security Debt Crisis
Why optimizing for speed over safety is leaving applications vulnerable, and how to fix it.
The post The Reality of Vibe Coding: AI Agents and the Security Debt Crisis appeared first on Towards Data Science.
A New Google AI Research Proposes Deep-Thinking Ratio to Improve LLM Accuracy While Cutting Total Inference Costs by Half
For the last few years, the AI world has followed a simple rule: if you want a Large Language Model (LLM) to solve a harder problem, make its Chain-of-Thought (CoT) longer. But new research from the University of Virginia and Google proves that ‘thinking long’ is not the same as ‘thinking hard’. The...
A key part of Agent Builder is its memory system. In this article we cover our rationale for prioritizing a memory system, technical details of how we built it, learnings from building the memory system, what the memory system enables, and discuss future work.
Is There a Community Edition of Palantir? Meet OpenPlanter: An Open Source Recursive AI Agent for Your Micro Surveillance Use Cases
The balance of power in the digital age is shifting. While governments and large corporations have long used data to track individuals, a new open-source project called OpenPlanter is giving that power back to the public. Created by a developer ‘Shin Megami Boson‘, OpenPlanter is a recursive-languag...
Google VP warns that two types of AI startups may not survive
As generative AI evolves, a Google VP warns that LLM wrappers and AI aggregators face mounting pressure, with shrinking margins and limited differentiation threatening their long-term viability.
Multi-tenancy, scheduling, and cost modeling on Kubernetes
The post Architecting GPUaaS for Enterprise AI On-Prem appeared first on Towards Data Science.
The creator economy’s ad revenue problem and India’s AI ambitions
The creator economy is evolving fast, and ad revenue alone isn’t cutting it anymore. YouTubers are launching product lines, acquiring startups, and building actual business empires. In fact, MrBeast’s company bought fintech startup Step, and his chocolate business is outearning his media arm. This i...
Anthropic-funded group backs candidate attacked by rival AI super PAC
Dueling pro-AI PACs have centered around backing or targeting one New York congressional bid: Alex Bores, whose RAISE Act requires AI developers to disclose safety protocols and report serious system misuse.