All entries

industrycristobal-valenzuela--x

Cristobal Valenzuela announced a deadline for RSVPs to the annual CVPR Friends Dinner scheduled for June 4th in Denver, featuring conversation, cocktails, and food. Interested attendees were directed

Model Releases

Latent Performance Profiling of Large Language Models

DGX agent

arXiv:2605.30018v1 Announce Type: new Abstract: Large language models (LLMs) frequently achieve impressive scores on standardized benchmarks, yet accuracy alone offers a limited view of their capabili

model-releasesarxiv-cs-cl

29 May 2026

Latent Terms: Dense Retrievers Contain Trivially Extractable BM25-ready Zipfian Vocabularies

arXiv:2605.29384v1 Announce Type: cross Abstract: We propose Latent Terms, a method revealing that models trained for dense retrieval, whether single- or multi-vector, learn representations that can t

tutorialsarxiv-cs-ai

Leak@k: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding

model-releasesarxiv-cs-lg

arXiv:2511.04934v3 Announce Type: replace Abstract: Unlearning in large language models (LLMs) is critical for regulatory compliance and for building ethical generative AI systems that avoid producing

Learn from A Rationalist: Distilling Intermediate Interpretable Rationales

arXiv:2601.22531v2 Announce Type: replace-cross Abstract: Because of the pervasive use of deep neural networks (DNNs), especially in high-stakes domains, the interpretability of DNNs has received incr

tutorialsarxiv-cs-ai

Learnable Assessment Skills for LLM-based Automated Scoring: Rubric Construction via Iterative Optimization

arXiv:2605.29274v1 Announce Type: new Abstract: LLM-based automated scoring approaches near-human performance, but scaling to new tasks remains bottlenecked by the per-item human configuration of upst

tutorialsarxiv-cs-cl

Learning A Simulation-based Visual Policy for Real-world Peg In Unseen Holes

arXiv:2205.04297v2 Announce Type: replace-cross Abstract: This paper proposes a learning-based visual peg-in-hole that enables training with several shapes in simulation, and adapting to arbitrary uns

Learning and Adaptation in Wire Arc Additive Manufacturing Bead Geometry Control

arXiv:2605.29144v1 Announce Type: new Abstract: Robotics Wire Arc Additive Manufacturing (WAAM) is governed by complex and nonlinear process dynamics coupling thermal field to the build geometry. The

tutorialsarxiv-cs-ro

Learning Context-Conditioned Predicate Semantics via Prototype Feedback

arXiv:2605.29610v1 Announce Type: cross Abstract: In scene graph generation, a central challenge is modeling polysemous predicates whose meanings shift across contexts. Prior approaches address this i

researcharxiv-cs-ai

Learning Design Skills as Memory Policies for Agentic Photonic Inverse Design

arXiv:2605.29421v1 Announce Type: new Abstract: Photonic crystal fiber (PCF) inverse design remains challenging because candidate geometries must satisfy coupled optical targets under expensive electr

Learning Representations from 3D Gaussian Splats

model-releasesarxiv-cs-cv

arXiv:2605.29549v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) is a recent approach for scene rendering. Although primarily designed for view synthesis, its potential for scene understan

Learning Robust and Task-Invariant Functional Representation from fMRI through Siamese Self-Supervised Learning

arXiv:2605.28990v1 Announce Type: new Abstract: Functional magnetic resonance imaging (fMRI) is a powerful tool for investigating human brain function. However, the high cost of data acquisition and t

tutorialsarxiv-cs-lg

Learning to Choose: An Empowerment-Guided Multi-Agent System with semantic communication for Adaptive Method Selection

arXiv:2605.30042v1 Announce Type: new Abstract: Automating scientific computing workflows requires more than generating executable code: autonomous systems must also select appropriate computational s

Learning to Extrapolate to New Tasks: A Relational Approach to Task Extrapolation

model-releasesarxiv-cs-lg

arXiv:2605.30132v1 Announce Type: new Abstract: Modern learning systems excel at interpolation but struggle to generalize to unseen tasks outside the training distribution's support. This failure occu

Learning to Feel Materials from Multisensory Tactile Data via Interpretable Models

arXiv:2605.29572v1 Announce Type: new Abstract: Human tactile perception of materials relies on complex multisensory touch cues, yet the relationship between low-level tactile signals and perceptual r

tutorialsarxiv-cs-ro

Learning to Perturb Hidden Representations for Generalizable Deep Learning

arXiv:2605.29525v1 Announce Type: new Abstract: Deep neural networks process data through a cascade of representations: input features, hidden activations, logits, and loss. While perturbations at the

researcharxiv-cs-lg

Local Ai

Learning to Solve PDEs on Neural Shape Representations

arXiv:2512.21311v2 Announce Type: replace Abstract: Solving partial differential equations (PDEs) on shapes underpins many shape analysis and engineering tasks; yet, prevailing PDE solvers operate on

local-aiarxiv-cs-lg

Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series

arXiv:2605.30292v1 Announce Type: cross Abstract: Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable, and predictor

researcharxiv-cs-lg

Lee Kuan Yew abolished trial by jury in Singapore after determining that it was too easy for defence lawyers to appeal to racial and religio…

Lee Kuan Yew abolished trial by jury in Singapore after determining that it was too easy for defence lawyers to appeal to racial and religious biases of juries in multicultural Singapore. He writes in

safetyelon-musk--x

Less is Enough: Synthesizing Diverse Data in LLM Feature Space with Sparse Autoencoders

arXiv:2602.10388v3 Announce Type: replace-cross Abstract: The diversity of post-training data is critical for effective downstream performance in large language models (LLMs). Many existing approaches

Less Is More: Elevating RAG via Performance-Driven Context Compression

arXiv:2508.19282v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm for improving the timeliness of knowledge updates and the factual acc

Leveraging Routing Dynamics in Mixture-of-Experts Models for Efficient Language Adaptation

arXiv:2605.29714v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are widely used to scale language models, yet their expert routing behavior and adaptation in a multilingual setting rem

Lexical categories of stem-forming roots in Mapudungun verb forms

arXiv:2502.07623v4 Announce Type: replace Abstract: After developing a computational system for morphological analysis of the Mapuche language, and evaluating it with texts from various authors and st

researcharxiv-cs-cl

LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs

arXiv:2605.29756v1 Announce Type: new Abstract: As large language models continue to scale, low-bit weight-only post-training quantization (PTQ) offers a practical solution to their memory-efficient d

researcharxiv-cs-ai

libhmm: A Modern C++20 Library for Hidden Markov Models with Correct MLE Emission M-Steps

model-releasesarxiv-cs-lg

arXiv:2605.29208v1 Announce Type: cross Abstract: We describe libhmm, a C++20 library for Hidden Markov Model parameter estimation, sequence decoding, and model selection. libhmm addresses two gaps in

Lightweight Complementary-Cue Fusion for Robust Video Face Forgery Detection

arXiv:2605.29092v1 Announce Type: new Abstract: Current face video forgery detectors use wide or dual-stream backbones. We show that a single, lightweight fusion of two handcrafted cues can achieve hi

researcharxiv-cs-cv

Lightweight Multimodal LLM-Enabled Cost-Effective Defect Grading of Power Transmission Equipment

arXiv:2605.28822v1 Announce Type: new Abstract: Defect grading of power transmission equipment (DGPTE) is crucial to the stability of electric energy transmission. Although existing machine learning m

researcharxiv-cs-cl

Tools

Links to original sources: https://simonwillison.net/2026/May/27/product-market-fit/#the-ai-failure-stories-around-this-are-pretty-thin

Simon Willison comments on the relative scarcity of well-documented AI product failure stories, suggesting that despite widespread predictions of AI disappointment, there are surprisingly few detailed

toolssimon-willison--x

LiteCoder-Terminal: Scaling Long-Horizon Terminal Environments for Learning Language Agents

arXiv:2605.29559v1 Announce Type: new Abstract: Mastering terminal environments requires language agents capable of multi-step planning, feedback-grounded execution, and dynamic state adaptation. Howe

LiveSVG: Zero-Shot SVG Animation via Video Generation

model-releasesarxiv-cs-cv

arXiv:2605.30174v1 Announce Type: new Abstract: We introduce LiveSVG, a zero-shot approach for generating Scalable Vector Graphics (SVG) animations using video diffusion models. Current SVG animation

llama.cpp now has an official website: https://llama.app Our goal is to make local AI accessible to everyone, and improving the user experie…

model-releasesclem-delangue--x

llama.cpp now has an official website: https://llama.app Our goal is to make local AI accessible to everyone, and improving the user experience is a big part of that. On the new landing page you’ll fi

LLM-Evolved Domain-Independent Heuristics for Symbolic AI Planning

arXiv:2605.29649v1 Announce Type: new Abstract: Heuristic search is the dominant paradigm in symbolic AI planning, and the strongest heuristics are the result of decades of work by planning researcher

LLM-Guided Future Hypotheses for Horizon-Aware Exploration in Multi-Step Robot Manipulation

arXiv:2605.29864v1 Announce Type: new Abstract: Multi-step robot manipulation requires acting under uncertainty about how the scene will evolve, making exploration and policy adaptation challenging. W

safetyarxiv-cs-ro

Agents

llm spend is starting to get really high... a key part of our LLM gateway is spend visibility and spend control sign up for the private beta…

llm spend is starting to get really high... a key part of our LLM gateway is spend visibility and spend control sign up for the private beta to try it out today! https://www.langchain.com/langsmith-ll

agentsharrison-chase--x

LLMBridge: An LLM Pipeline for End-to-end Referential Bridging Resolution in English

arXiv:2605.29048v1 Announce Type: new Abstract: In this paper, we introduce LLMBridge, a new LLM based system for the task of end-to-end referential bridging resolution in English. Our bridging resolu

researcharxiv-cs-cl

LLMSurgeon: Diagnosing Data Mixture of Large Language Models

arXiv:2605.30348v1 Announce Type: cross Abstract: The pretraining data mixture of Large Language Models (LLMs) constitutes their 'digital DNA', shaping model behaviors, capabilities, and failure modes

researcharxiv-cs-ai

LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback

arXiv:2605.30273v1 Announce Type: cross Abstract: Large language models (LLMs) show promise in generating supportive responses for mental health queries, but improving their usefulness, empathy, and s

Local Ai

Local: https://github.com/Comfy-Org/workflow_templates/blob/main/templates/api_openrouter_llm.json

This template provides a ComfyUI workflow configuration for integrating OpenRouter's API to enable large language model (LLM) capabilities within ComfyUI's node-based interface. It demonstrates how to

local-aicomfyui--x

Local Ai

Locally Coherent, Globally Incoherent: Bounding Compositional Incoherence in Multi-Component LLM Agents

arXiv:2605.30335v1 Announce Type: new Abstract: Multi-component LLM agents assemble probabilistic claims from components that each see only part of a joint problem; the composition can violate basic p

local-aiarxiv-cs-ai

LoCoT2V-Bench: Benchmarking Long-Form and Complex Text-to-Video Generation

arXiv:2510.26412v3 Announce Type: replace-cross Abstract: Recent advances in text-to-video generation have achieved impressive performance on short clips, yet evaluating long-form generation under com

LogDx-CI: Benchmarking Log Reduction Tools for LLM Root-Cause Diagnosis

arXiv:2605.28876v1 Announce Type: cross Abstract: CI failure logs are large (median 5k lines, max 200k in this corpus) and noisy. Coding agents that try to debug them depend on an upstream tool to red

LoMo: Local Modality Substitution for Deeper Vision-Language Fusion

arXiv:2605.30265v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved substantial progress across a wide range of understanding and reasoning tasks, driven by large-scale image

safetyarxiv-cs-cl

Industry

London-based Inherent, which aims to combine human scientific research with AI to produce innovations, emerges from stealth with $50M led by Index Ventures (Martin Coulter/Sifted)

Martin Coulter / Sifted: London-based Inherent, which aims to combine human scientific research with AI to produce innovations, emerges from stealth with $50M led by Index Ventures — London-based Inhe

industrytechmeme

Long-Context Modeling with Dynamic Hierarchical Sparse Attention for Memory-Constrained LLM Inference

arXiv:2510.24606v2 Announce Type: replace Abstract: The quadratic cost of attention limits the scalability of long-context LLMs, especially under limited hardware memory budgets. While attention is of

Applications

Looking around you: external information enhances representations for event sequences

arXiv:2502.10205v3 Announce Type: replace Abstract: Representation learning produces models in different domains, such as store purchases, client transactions, and general people's behavior. However,

applicationsarxiv-cs-lg

Looking Beyond Text: Reducing Language bias in Large Vision-Language Models via Multimodal Dual-Attention and Soft-Image Guidance

arXiv:2411.14279v2 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) have achieved impressive results in various vision-language tasks. However, despite showing promising per

safetyarxiv-cs-cl

Loong: A Human-Like Long Document Translation Agent with Observe-and-Act Adaptive Context Selection

arXiv:2605.30274v1 Announce Type: cross Abstract: Document-level translation remains one of the most challenging tasks for large language models, which are constrained by limited context windows that

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation

arXiv:2605.29280v1 Announce Type: cross Abstract: Knowledge distillation (KD) transfers a single scalar prediction from a large foundation model (FM) to compact vertical models (VMs), suffering from d