arXiv Machine Learning
Jun 17
Turning music identification into a neural forward pass
arXiv:2606. 17301v1 Announce Type: cross Abstract: Search, a foundational operation in computer science, maps a query to a matching item in a collection.
Large language models
Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv AI
Jun 17
LLM Consumer Behavior Theory: Foundations of a Novel Research Field
arXiv:2606. 18005v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents that make consumption decisions on behalf of users.
arXiv AI
Jun 17
Security and Privacy Prompts in the Wild: What Users Ask LLMs and How LLMs Respond
arXiv:2606. 18062v1 Announce Type: cross Abstract: Large language models (LLMs) are widely used to fulfill users' information needs; users ask LLMs about the weather, pose educational questions, and consult them for legal assistance.
arXiv AI
Jun 17
EngTrace: A Symbolic Benchmark for Verifiable Process Supervision of Engineering Reasoning
arXiv:2511. 01650v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly entering specialized, safety-critical engineering workflows governed by strict quantitative standards and immutable physical laws, making rigorous evaluation of their reasoning capabilities imperative.
arXiv AI
Jun 17
DiagFlowBench: Evaluating How Language Models Handle Off-Procedure Inputs in Grounded Diagnostic Dialogue
arXiv:2606. 17904v1 Announce Type: new Abstract: Language models increasingly serve as advisory systems in maintenance operations.
arXiv AI
Jun 17
PreAct: Computer-Using Agents that Get Faster on Repeated Tasks
arXiv:2606. 17929v1 Announce Type: new Abstract: Computer-using agents drive real software through the screen -- clicking and typing -- but they solve every task from scratch: asked to repeat a task, an agent re-reads the screen, re-reasons every tap, and pays the full cost again.
arXiv AI
Jun 17
DecoSearch: Complexity-Aware Routing and Plan-Level Repair for Text-to-SQL
arXiv:2606. 17821v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in translating natural language to SQL, yet existing methods still falter on complex queries requiring multi-step, data-aware reasoning.
arXiv AI
Jun 17
LLM-as-Judge in Education: A Curriculum-Grounded Marking Pipeline
arXiv:2606. 17507v1 Announce Type: new Abstract: Generative AI and large language models (LLMs) are increasingly applied to question generation and automated assessment.
arXiv AI
Jun 17
How Inference Compute Shapes Frontier LLM Evaluation
arXiv:2606. 17930v1 Announce Type: new Abstract: AI evaluations are shifting toward harder tasks that benefit from longer trajectories involving tool use and iterative problem solving.
arXiv Machine Learning
Jun 17
On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies
arXiv:2606. 17276v1 Announce Type: cross Abstract: Generative recommendation (GR) has emerged as a promising direction for recommender systems.
arXiv AI
Jun 17
The Discrete-Log Clock: How a Transformer Learns Modular Multiplication
arXiv:2606. 17399v1 Announce Type: cross Abstract: When small transformers grok modular multiplication, prior work reports that the learned embedding has a "dense" Fourier spectrum requiring all frequencies.
arXiv Machine Learning
Jun 17
DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels
arXiv:2602. 11715v2 Announce Type: replace Abstract: Diffusion large language models (dLLMs) have emerged as a compelling alternative to autoregressive (AR) LLMs, owing to their capacity for parallel token generation.
arXiv AI
Jun 17
Learning-Infused Formal Reasoning: From Contract Synthesis to Artifact Reuse and Formal Semantics
arXiv:2602. 02881v2 Announce Type: replace-cross Abstract: This paper articulates a long-term research vision for formal methods at the intersection with artificial intelligence, outlining multiple conceptual and technical dimensions and reporting on our ongoing work toward realising this vision.
arXiv AI
Jun 17
Teaching Values to Machines: Simulating Human-Like Behavior in LLMs
arXiv:2605. 30036v2 Announce Type: replace Abstract: Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure.
arXiv AI
Jun 17
A Multifaceted Analysis of Social Biases in Large Language Models
arXiv:2512. 15792v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making.
arXiv AI
Jun 17
WEQA: Wearable hEalth Question Answering with Query-Adaptive Agentic Reasoning
arXiv:2606. 18147v1 Announce Type: new Abstract: Language models are remarkably capable at medical question answering, in some cases surpassing the accuracy of general physicians.
arXiv Machine Learning
Jun 17
Toward Controllable Catalyst Inverse Design via Large-Scale Autoregressive Pretraining
arXiv:2606. 17445v1 Announce Type: new Abstract: Inverse design of heterogeneous catalysts remains challenging because catalyst surfaces exhibit substantial structural complexity with coupled surface-adsorbate interactions across a vast chemical space that is difficult to explore efficiently through conventional screening alone.
arXiv AI
Jun 17
Decoding Hidden Deception in Reasoning LLMs: Activation Explainers for Deception Auditing
arXiv:2606. 17478v1 Announce Type: cross Abstract: As LLMs acquire stronger reasoning capabilities, deceptive behavior becomes an increasingly serious safety concern.
arXiv AI
Jun 17
LLM-Powered Multi-Agent System for Automated Crypto Portfolio Management
arXiv:2501. 00826v3 Announce Type: replace-cross Abstract: Cryptocurrency portfolio management requires the fusion of heterogeneous multi-modal signals, including structured price and on-chain time series, unstructured news text, and technical indicators, under high-volatility and real-time constraints.
arXiv AI
Jun 17
Beyond Domains: Reusing Web Skills via Transferable Interaction Patterns
arXiv:2606. 17645v1 Announce Type: new Abstract: Large language model (LLM) web agents are usually deployed as tool callers: each turn, the model reads a fresh page observation and emits one structured tool action.