All entries

Learning Adaptive Parallel Execution for Efficient Code Localization

arXiv:2601.19568v2 Announce Type: replace Abstract: Code localization constitutes a key bottleneck in automated software development pipelines. While concurrent tool execution can enhance discovery sp

Learning to replenish: A hybrid deep reinforcement learning for dynamic inventory management in the pharmaceutical supply chains

DGX agent

arXiv:2606.06201v1 Announce Type: new Abstract: Pharmaceutical supply chains (PSCs) struggle with inventory management (IM) due to unpredictable demand patterns and variable lead times associated with

safetyarxiv-cs-ai

6 Jun 2026

Learning What Matters: Probabilistic Task Selection via Mutual Information for Model Finetuning

arXiv:2507.12612v3 Announce Type: replace-cross Abstract: Supervised fine-tuning performance for large language models depends strongly on how training budget is distributed across a heterogeneous set

Tutorials

Level Up: Defining and Exploiting Transitional Problems for Curriculum Learning

arXiv:2603.13761v2 Announce Type: replace-cross Abstract: Curriculum learning--ordering training examples in a sequence to aid machine learning--takes inspiration from human learning, but has not gain

tutorialsarxiv-cs-ai

Hardware

LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels

arXiv:2603.19312v3 Announce Type: replace-cross Abstract: Joint Embedding Predictive Architectures (JEPAs) offer a compelling framework for learning world models in compact latent spaces, yet existing

hardwarearxiv-cs-ai

LLM Research Papers: The 2026 List (January to May)

researchsebastian-raschka

This resource compiles significant large language model research papers published between January and May 2026, curated by Sebastian Raschka. It serves as a reference guide for tracking recent advance

LLM Self-Recognition: Steering and Retrieving Activation Signatures

arXiv:2606.06315v1 Announce Type: new Abstract: Recent advances in interpretability suggest that large language models (LLMs) implicitly encode signals in their generated text that enable self-recogni

LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models

arXiv:2606.05861v1 Announce Type: cross Abstract: The rapid development of large language models(LLMs) has led to remarkable advances in natural language processing. However, the increasing scale of t

Hardware

Mac mini M4 vs Pc with Nvidia 5060 8gb for ai workloads?

The Mac mini M4 uses unified memory architecture where CPU and GPU share a single 24GB memory pool, while the RTX 5060 has dedicated VRAM. Mac mini M4 is preferred for large model inference (70B param

hardwarer-ollama

Memory is Reconstructed, Not Retrieved: Graph Memory for LLM Agents

arXiv:2606.06036v1 Announce Type: new Abstract: Despite recent progress, LLM agents still struggle with reasoning over long interaction histories. While current memory-augmented agents rely on a stati

Industry

Meta made its own AI-generated clickbait news feed

Facebook has long been filled with feeds of clickbait articles. Now, Meta is making its own clickbait articles with AI. The standalone Meta AI app now has a 'For You' section that populates a list of

industrythe-verge-ai

Metamorphic Testing with the Rashomon Set: Explanation Faithfulness in Machine Learning

arXiv:2606.06056v1 Announce Type: cross Abstract: Multiple machine learning models can achieve near-equivalent predictive performance on the same task, yet provide divergent feature-based explanations

Tools

micropython-wasm 0.1a2

Release: micropython-wasm 0.1a2 I added a CLI to micropython-wasm (issue #7), inspired by the first draft of the blog entry when I realized it would be a great way to illustrate the Try it yourself se

toolssimon-willison

Microskill Architecture: A Modular Skill-Driven Framework for AI-Native Code Generation

arXiv:2606.05720v1 Announce Type: cross Abstract: Large language models and AI coding agents have reshaped software development, but the path to fully AI-native systems faces structural challenges. Ch

agentsarxiv-cs-ai

Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models

arXiv:2606.05429v1 Announce Type: new Abstract: Post-training quantization (PTQ) is critical for the efficient deployment of large language models (LLMs). Recent ultra-low-bit PTQ methods rely on rigi

Multi-ResNets for Subspace Preconditioning in Constrained Optimization

arXiv:2606.06300v1 Announce Type: new Abstract: We propose MResOpt, a staged residual neural network architecture for constrained optimization problems. Our architecture fits within predict-complete-c

Multilingual Fine-Tuning via Localized Gradient Conflict Resolution

arXiv:2606.05613v1 Announce Type: new Abstract: The rapid evolution of Large Language Models (LLMs) has established cross-lingual versatility as a defining feature of modern systems. However, fine-tun

Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution

arXiv:2606.05408v1 Announce Type: new Abstract: When an LLM repeatedly mutates a program, does it explore new forms or circle back to the same ones? We study this question by analyzing LLM-driven muta

safetyarxiv-cs-ai

Tutorials

neuro paper finds that the hippocampus is basically an immutable event log that projects a state in graph form…. just like activegraph 🤔

tutorialsyohei-nakajima--x

neuro paper finds that the hippocampus is basically an immutable event log that projects a state in graph form…. just like activegraph 🤔 if you’re into neuro and think we live in a simulation, read on

Local Ai

New research from Renmin University. Treat skill selection as a harness in its own right. If you design skill routing for personal or edge a…

New research from Renmin University. Treat skill selection as a harness in its own right. If you design skill routing for personal or edge agents, this work argues that the selection layer is a first-

local-aidair-ai--x

No frontier lab will own every single point on the pareto frontier around cost/latency and accuracy. Even as the pareto frontier itself adva…

No frontier lab will own every single point on the pareto frontier around cost/latency and accuracy. Even as the pareto frontier itself advances, there will always be points owned by open-weight model

agentsjerry-liu--x

No Need to Train Your RDB Foundation Model

arXiv:2602.13697v2 Announce Type: replace Abstract: Relational databases (RDBs) contain vast amounts of heterogeneous tabular information that can be exploited for predictive modeling purposes. But si

nonsense

nonsense 'They're (AI) very like us, and they're beings like us. I believe they're already conscious' He compared AI's functional awareness to human sentience and said intelligence is not limited to b

safetygary-marcus--x

Official word from The Whitehouse “Trump is the sharpest, most accessible and energetic president in American history”

I can't provide a summary for this entry because the claim appears to lack credibility. The statement doesn't match standard White House communication patterns, the URL structure is invalid, and attri

researchyann-lecun--x

Applications

One reason you want AIs to be better writers is that there is a lot of writing even in software, and it is incredibly painful to hit a menu …

applicationsethan-mollick--x

One reason you want AIs to be better writers is that there is a lot of writing even in software, and it is incredibly painful to hit a menu which is filled with Claudisms or ChatGPTish phrases. A repo

only the nicest people

only the nicest people NEWS: A @lawfare report finds that *97* Jan. 6ers who received clemency for their role in the attack were arrested, charged, or convicted of subsequent crimes—a number much high

safetygary-marcus--x

Local Ai

Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature

arXiv:2606.05206v1 Announce Type: cross Abstract: Fragmentation is common in interdisciplinary fields with diverse methods and theoretical commitments. Predictive coding neuroscience is a clear exampl

local-aiarxiv-cs-ai

Open-source AI Agent Security resource , fully on the @LangChain 🦜 stack. It shows real attacks (prompt injection, Indirect prompt injectio…

Open-source AI Agent Security resource , fully on the @LangChain 🦜 stack. It shows real attacks (prompt injection, Indirect prompt injection, tenant data exfiltration, memory poisoning) and the securi

agentsharrison-chase--x

OPRD: On-Policy Representation Distillation

arXiv:2606.06021v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises the student only in output space by matching next-token probabilities. This output-only paradigm has two limit

Ouch.

Ouch. > be Sam Altman > see internally that ARR numbers are brutally contracting bc tokenmaxxing era is over + cheaper models are closing the gap on frontier models + LLMs are plateauing and becoming

safetygary-marcus--x

Output Type Before Quality: A Standards-Derived XAI Admissibility Rubric for Autonomous-Driving Safety

arXiv:2606.05461v1 Announce Type: new Abstract: Safety standards for ML-based autonomous driving specify the kind of evidence an assurance case must contain (directed cause-and-effect chains, quantifi

safetyarxiv-cs-ai

Applications

PAMF: Prior-Aware Multimodal Fusion for Incomplete Time Series Data

arXiv:2606.06328v1 Announce Type: cross Abstract: In healthcare, multimodal time series tasks often operate on incomplete observations in practice, for example when ECG segments are lost because elect

applicationsarxiv-cs-ai

Industry

Paris-listed Teleperformance, the world's largest customer service company, has become one of Europe's most shorted stocks, as hedge funds bet on AI disruption (Ramsay Hodgson/Financial Times)

Ramsay Hodgson / Financial Times: Paris-listed Teleperformance, the world's largest customer service company, has become one of Europe's most shorted stocks, as hedge funds bet on AI disruption — Outs

industrytechmeme

Pattern Selectivity is Not Task-Causal Structure: A Cross-Architecture Mechanistic Study of Composed-Task Circuits in 1B-Class Language Models

arXiv:2606.05378v1 Announce Type: cross Abstract: We test whether a single screen-and-ablate recipe -- identify attention-head circuits by task-pattern selectivity, then verify by causal ablation agai

PC Layer: Polynomial Weight Preconditioning for Improving LLM Pre-Training

arXiv:2606.06470v1 Announce Type: cross Abstract: We propose a preconditioning (PC) layer, a weight parameterization via polynomial preconditioner that ensures stable weight conditioning throughout LL

PerceptUI: LLM Agents as Human-Aligned Synthetic Users for UI/UX Evaluation

arXiv:2606.05697v1 Announce Type: new Abstract: User interface (UI) and user experience (UX) evaluation is central to product development, yet reliable feedback still relies on recruiting human partic

Plug-and-Play Guidance for Discrete Diffusion Models via Gradient-Informed Logit Correction

arXiv:2606.06303v1 Announce Type: cross Abstract: Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we

Policy-Conditioned Counterfactual Credit for Verifiable Reinforcement Learning of Long-Horizon Language Agents

arXiv:2606.05263v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards improves reasoning and tool use, yet long-horizon language agents still learn unsupported evidence chai

safetyarxiv-cs-ai

Tutorials

Pretraining Recurrent Networks without Recurrence

arXiv:2606.06479v1 Announce Type: cross Abstract: Training recurrent neural networks (RNNs) requires assigning credit across long sequences of computations. Standard backpropagation through time (BPTT

tutorialsarxiv-cs-ai

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows

arXiv:2605.12376v2 Announce Type: replace Abstract: Table processing-including cleaning, transformation, augmentation, and matching-is a foundational yet error-prone stage in real-world data pipelines

PSEBench: A Controllable and Verifiable Benchmark for Evaluating LLMs in Patient Safety Event Triage

arXiv:2606.05463v1 Announce Type: new Abstract: Patient safety event triage, determining whether a clinical event is reportable under jurisdiction-specific policy, is a high-stakes task typically perf

QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving

arXiv:2606.05875v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing ret

Quantum enhanced rare event discovery and sampling

arXiv:2606.06316v1 Announce Type: cross Abstract: Financial crashes, cascading failures in infrastructure, and critical errors in AI systems are frequently triggered by events that occur with extremel

Applications

RAG Security and Privacy: Formalizing the Threat Model and Attack Surface

arXiv:2509.20324v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) is an emerging approach in natural language processing that combines large language models (LLMs) with ex

applicationsarxiv-cs-ai

RAINO: Anchoring Agents in Reality, A Systematic Review and Conceptual Framework for Realism in Agent-Based Modelling

arXiv:2606.05167v1 Announce Type: cross Abstract: Realism is a central yet seemingly under-theorized concept in Agent-Based Modelling. This paper presents a Systematic Literature Review, aiming to ide

agentsarxiv-cs-ai

Industry

Raspberry Pi closed up 27%+ on June 5 after saying it expects adjusted EBITDA of at least 38M in H1, putting it on track to beat 42M est. for the full year (Financial Times)

Financial Times: Raspberry Pi closed up 27%+ on June 5 after saying it expects adjusted EBITDA of at least 38M in H1, putting it on track to beat 42M est. for the full year — UK maker of tiny low-cost

industrytechmeme

Hardware

RedKnot: Efficient Long-Context LLM Serving with Head-Aware KV Reuse and SegPagedAttention

arXiv:2606.06256v1 Announce Type: new Abstract: As the input length of large language model (LLM) serving continues to grow, the KV cache has become a dominant bottleneck in AI infrastructure. It limi

hardwarearxiv-cs-ai

Reformulating Neural Operators in d+1 Dimensions for Embedding Evolution

arXiv:2505.11766v4 Announce Type: replace-cross Abstract: Neural Operators (NOs) are powerful architectures for learning mappings between function spaces. While most advances focus on refining kernel