All entries

Assessing VLM Reliability for Medical Image Quality Evaluation Under Corruption and Bias

arXiv:2607.01973v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly applied in medical tasks such as pathology description, report generation, and visual question answerin

Applications

At Cohere we deploy our models directly to our customers, instead of them sending data to us. It makes our job harder, but their business mo…

DGX agent

At Cohere we deploy our models directly to our customers, instead of them sending data to us. It makes our job harder, but their business more secure: “When you’re using a consumer app, they are using

applicationscohere--x

3 Jul 2026

Tools

'At least this felt ambitious until fable chewed through each of my requests like it was nothing...'

'At least this felt ambitious until fable chewed through each of my requests like it was nothing...' @simonw I made this 3D video infographic explaining the AuthaGraph map projection, with population

toolssimon-willison--x

AthDGC: An Open Diachronic Greek Treebank with Indo-European Parallels

arXiv:2606.15510v2 Announce Type: replace Abstract: AthDGC ('Athens-PROIEL') is an open, end-to-end workflow and dataset. It is, to the best of our knowledge, the first openly licensed dependency-pars

safetyarxiv-cs-cl

Atomic Task Graph: A Unified Framework for Agentic Planning and Execution

arXiv:2607.01942v1 Announce Type: new Abstract: LLM-based agents have shown strong potential for solving complex multi-step tasks, yet existing performance improvements often rely on either scaling to

agentsarxiv-cs-ai

Audio-Based Understanding of Audiobook Narration Appeal

arXiv:2607.02473v1 Announce Type: new Abstract: Narration is central to the audiobook listening experience, shaping how listeners engage with and understand the content. This work explores how narrati

researcharxiv-cs-cl

Auto-FL-Research: Agentic Search for Federated Learning Algorithms

arXiv:2607.01366v1 Announce Type: new Abstract: Federated learning (FL) research often depends on many small but consequential algorithmic choices: optimizer variants, server aggregation rules, local

local-aiarxiv-cs-ai

Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach

arXiv:2607.02432v1 Announce Type: new Abstract: Scalable and reliable grading of command-line examinations remains a challenge in computing education, where rising enrolments make manual marking diffi

Autonomous discovery of traffic laws with AI traffic scientists

arXiv:2607.01639v1 Announce Type: new Abstract: Universal traffic laws describe recurrent patterns in congestion, mobility and driving behavior across cities, providing a scientific basis for transpor

agentsarxiv-cs-ai

Autorelevance function and other feature relevance measures for univariate time series

arXiv:2607.01959v1 Announce Type: cross Abstract: We propose a model agnostic methodology to measure lag relevance in machine learning forecasting models applied to univariate time series. Particularl

researcharxiv-cs-lg

b9862

local-aillama-cpp-releases

B9862 is a continuous build-tagged release from llama.cpp , the open-source C/C++ LLM inference engine. Llama.cpp is the inference engine that powers most of the local-AI ecosystem, including tools li

b9864

local-aillama-cpp-releases

llama.cpp is a tool for LLM inference in C/C++ and b9864 is a release version tag from the ggml-org/llama.cpp GitHub repository. Based on the release numbering pattern and project scope, this release

b9870

local-aillama-cpp-releases

b9870 is a llama.cpp release dated July 3, 2026 , which includes fixes for StepFun parser chat handling to address long reasoning loops . The release provides pre-built binaries for multiple platforms

BALF: Budgeted Activation-Aware Low-Rank Factorization for Fine-Tuning-Free Model Compression

arXiv:2509.25136v3 Announce Type: replace Abstract: Activation-aware low-rank factorization techniques yield strong compression results but are generally confined to linear layers, while existing whit

BamiBERT: A New BERT-based Language Model for Vietnamese

arXiv:2607.02259v1 Announce Type: new Abstract: In this paper, we introduce BamiBERT, a new BERT-based pre-trained language model for Vietnamese that addresses key limitations of PhoBERT -- the curren

researcharxiv-cs-cl

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation

arXiv:2607.02182v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable reasoning capabilities, but their task-specific fine-tuning is notoriously plagued by overconfidence,

Behind the Refusal: Determining Guardrail Activation via Behavioral Monitoring

arXiv:2607.02121v1 Announce Type: cross Abstract: As Large Language Models (LLMs) and agentic systems become integrated into real-world applications, ensuring their safety and security is critical. Gu

Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification

arXiv:2607.01272v1 Announce Type: cross Abstract: Deploying 3D point cloud analysis in privacy-sensitive, resource-constrained settings faces two barriers: data cannot be centralized, and models must

Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials

arXiv:2607.02499v1 Announce Type: cross Abstract: Machine learning interatomic potentials (MLIPs) have become a hallmark of AI for scientific simulation. While efforts on new architectures and dataset

Beyond Detection: Redesigning Assessment and Governande of Generative AI at the Universidad Politecnica de Madrid (UPM)

arXiv:2607.01255v1 Announce Type: cross Abstract: Universities have responded to generative artificial intelligence (GenAI) in noticeably different ways, both internationally and within Spain. So far,

Beyond Gradient-Based Attacks: Adversarial Robustness and Explainability Stability in Cybersecurity Classifiers

arXiv:2607.01679v1 Announce Type: cross Abstract: Adversarial attacks on cybersecurity classifiers pose a dual threat: degrading predictions and destabilising the SHAP-based explanations that security

Beyond Next-Token Prediction: An RLVR Proof of Concept for Tool-Use Agents on Atlassian Workflows

arXiv:2607.01465v1 Announce Type: new Abstract: Large language models are trained to predict the next token, not to act inside a specific API. In niche enterprise SaaS workflows -- where success means

Beyond Pixel Diffs: Benchmarking Image Change Captioning for Web UI Visual Regression Testing

arXiv:2607.01728v1 Announce Type: cross Abstract: Visual regression testing (VRT) is a standard quality assurance step in modern software release pipelines. On every change, it re-renders user interfa

Beyond Skepticism: Evaluating LLMs Pedagogical Intent Reasoning with the Adaptive Pedagogical Vigilance Framework

arXiv:2607.01581v1 Announce Type: new Abstract: The capacity of Large Language Models (LLMs) to reason about pedagogical intent within instructional communication remains underexplored, particularly i

Beyond Supervised Clarification: Input Rewriting with LLMs for Dialogue Discourse Parsing

arXiv:2607.01964v1 Announce Type: new Abstract: Rewriting inputs to improve frozen downstream models has become a common strategy in modern NLP pipelines. Prior work on incremental dialogue discourse

agentsarxiv-cs-cl

Beyond the Performance Illusion: Structure-Aware Stratified Partitioning and Curriculum Distributionally Robust Optimization for Spatially Correlated Domains

arXiv:2607.02055v1 Announce Type: cross Abstract: Performance evaluation in AI systems commonly assumes that random dataset splits produce independent and identically distributed (i.i.d.) subsets. We

Applications

Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search

arXiv:2607.01387v1 Announce Type: cross Abstract: Recommender systems are vital in helping users navigate vast amounts of information, offering personalized suggestions and effective explanations for

applicationsarxiv-cs-lg

BIFROST: Bridging Invariant Feature Representation for Observation-space Sim2Real Transfer

arXiv:2607.01410v1 Announce Type: cross Abstract: Sim2real transfer for robot policy learning suffers due to mismatch between simulation and reality. Existing methods typically address each gap in iso

safetyarxiv-cs-lg

Black-Box Inference of LLM Architectural Properties with Restrictive API Access

arXiv:2607.01313v1 Announce Type: cross Abstract: In practice, most commercial LLM providers do not publicly release details of underlying LLM architectures. However, prior work has shown that given l

Applications

Blackstone's QTS abandons plans to build its portion of a 2,100-acre data center campus in Virginia, following years of local opposition and legal challenges (Dawn Lim/Bloomberg)

Dawn Lim / Bloomberg: Blackstone's QTS abandons plans to build its portion of a 2,100-acre data center campus in Virginia, following years of local opposition and legal challenges — Blackstone Inc.'s

applicationstechmeme

Born Discrete, Made Smooth: Variational Formulation of Shallow Neural Networks

arXiv:2607.02003v1 Announce Type: cross Abstract: Although neural networks are remarkably effective, their underlying optimization principles remain theoretically elusive, often characterized by non-c

Boundary-Aware Quantization: Finite-Scale Decision Geometry of Neural Classifiers

arXiv:2607.01478v1 Announce Type: cross Abstract: We measured quantization-induced decision-boundary changes using local logit-margin radii, first-order boundary displacement, normal variation, slice-

BOUNDARY_SYNC: Measuring Communication-Induced Representational Coupling in Multi-Agent LLM Systems

arXiv:2607.01600v1 Announce Type: cross Abstract: As large language models (LLMs) are deployed as communicating agents, does inter-agent communication cause outputs to converge? We introduce BOUNDARY_

Brazenly self-serving: the Trump family’s earnings during his first year in office 'have moved him into an echelon of enrichment more associ…

Brazenly self-serving: the Trump family’s earnings during his first year in office 'have moved him into an echelon of enrichment more associated with strongmen in Russia and Turkey.' https://trib.al/i

researchyann-lecun--x

Breaking Safety at the Token Boundary: How BPE Tokenization Creates Exploitable Gaps in LLM Alignment

arXiv:2607.01239v1 Announce Type: cross Abstract: Character-level perturbations bypass safety alignment in modern LLMs despite leaving prompts human-readable. We identify and test a central structural

BRIDGE: Predicting Human Task Completion Time From Model Performance

arXiv:2602.07267v2 Announce Type: replace Abstract: Evaluating the real-world capabilities of AI systems requires grounding benchmark performance in human-interpretable measures of task difficulty. Ex

Bridge-WA: Predicting Where and How the World Changes for Robotic Action

arXiv:2607.02195v1 Announce Type: new Abstract: General-purpose vision-language-action models benefit from large vision-language priors, but effective manipulation also requires anticipating action-re

local-aiarxiv-cs-ro

Bringing Agentic Search to Earth Observation Data Discovery

arXiv:2607.02387v1 Announce Type: cross Abstract: NASA and its data centers hold thousands of geoscience datasets and tools like Worldview, Giovanni, the Science Discovery Engine, and Harmony. Finding

BuilderBench: The Building Blocks of Intelligent Agents

arXiv:2510.06288v4 Announce Type: replace Abstract: Today's AI models learn primarily through mimicry and refining, so it is not surprising that they struggle to solve problems beyond the limits set b

CALM: Interpretable Cross-Modal Alignment for Biomarker Discovery from Unpaired Data

arXiv:2607.01656v1 Announce Type: new Abstract: The interaction between brain structure and genetic influences is key to understanding neuropsychiatric disorders. However, most large-scale datasets ar

safetyarxiv-cs-lg

CamoNAS: Neural Architecture Search for Enhanced Camouflaged Object Detection

arXiv:2607.01870v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to locate and segment objects that blend into their surroundings, presenting challenges due to weak edge cues an

Industry

Can anyone get me tickets for the world-cup quarter-final in Miami next week?

Clem Delangue posted a request on X asking if anyone could help obtain tickets for a World Cup quarter-final match scheduled to take place in Miami the following week. The post appears to be a public

industryclem-delangue--x

Can coding-agents replicate scientific ML papers? We know this is possible because we can already do this @dair_ai. Still a great read. So t…

Can coding-agents replicate scientific ML papers? We know this is possible because we can already do this @dair_ai. Still a great read. So they try to replicate an ML paper from its materials alone. T

agentsdair-ai--x

Can Language Models Actually Retrieve In-Context? Drowning in Documents at Million Token Scale

arXiv:2607.01538v1 Announce Type: new Abstract: Language models (LMs) raise an intriguing alternative to vector-based retrieval: conditioning on an in-context corpus and directly generating a relevant

researcharxiv-cs-cl

CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation

arXiv:2603.22435v2 Announce Type: replace-cross Abstract: 'Code-as-Policy' considers how executable code can complement data-intensive Vision-Language-Action (VLA) methods, yet their effectiveness as

Causal Explanations for Image Classifiers

arXiv:2411.08875v4 Announce Type: replace Abstract: Existing algorithms for explaining the output of image classifiers use different definitions of explanations and a variety of techniques to find the

CausalSteward: An Agentic Divide-Conquer-Combine Copilot for Causal Discovery

arXiv:2607.01936v1 Announce Type: cross Abstract: Learning causal models from high-dimensional data is a significant challenge, particularly in real-world settings where violations of core assumptions

agentsarxiv-cs-ai

Certified World Models as Sensing Clocks: Drift-Aware Deadlines for Active Perception

arXiv:2607.01537v1 Announce Type: new Abstract: Certified world models estimate how long their predictions remain valid. We turn this validity horizon into an operational sensing clock: a rule for whe

agentsarxiv-cs-lg