All entries

Communication-Efficient Federated Fine-Tuning

model-releasesarxiv-cs-lg

arXiv:2505.04535v3 Announce Type: replace Abstract: Federated Learning (FL) enables the utilization of vast, previously inaccessible data sources. At the same time, pre-trained Language Models (LMs) h

Industry

Companies are rethinking the contact center to deliver outcomes — and empathy — at scale

DGX agent

Contact center AI transformation is accelerating in financial services as new innovations close the gap between surface-level metrics and genuine customer understanding in high-stakes interactions. Fo

industrysiliconangle

15 May 2026

company that steals IP urges US government not to allow others to steal their IP

company that steals IP urges US government not to allow others to steal their IP Anthropic drops a paper on the US-China AI race They believe the US and its allies may be able to lock in a 12-24 month

safetygary-marcus--x

Comparative Evaluation of Machine Learning Approaches for Minority-Class Financial Distress Prediction Under Class Imbalance Constraints

arXiv:2605.14067v1 Announce Type: new Abstract: Financial distress prediction remains a significant challenge in enterprise risk analysis due to the highly imbalanced nature of real-world financial da

applicationsarxiv-cs-lg

Comparing Developer and LLM Biases in Code Evaluation

arXiv:2603.24586v2 Announce Type: replace-cross Abstract: As LLMs are increasingly used as judges in code applications, they should be evaluated in realistic interactive settings that capture partial

safetyarxiv-cs-cl

Complacent, Not Sycophantic: Reframing Large Language Models and Designing AI Literacy for Complacent Machines

arXiv:2605.14544v1 Announce Type: new Abstract: Large language models are often described as sycophantic, in the sense that they appear to flatter users or mirror their beliefs. We argue that this lab

Composable Crystals: Controllable Materials Discovery via Concept Learning

arXiv:2605.14769v1 Announce Type: new Abstract: De novo crystal generation, a central task in materials discovery, aims to generate crystals that are simultaneously valid, stable, unique, and novel. E

local-aiarxiv-cs-lg

Compositional Sparsity as an Inductive Bias for Neural Architecture Design

arXiv:2605.14764v1 Announce Type: cross Abstract: Identifying the structural priors that enable Deep Neural Networks (DNNs) to overcome the curse of dimensionality is a fundamental challenge in machin

Compositional Video Generation via Inference-Time Guidance

arXiv:2605.14988v1 Announce Type: new Abstract: Text-to-video diffusion models generate realistic videos, but often fail on prompts requiring fine-grained compositional understanding, such as relation

Computational Imaging Priors for Wireless Capsule Endoscopy: Monte Carlo-Guided Hemoglobin Mapping for Rare-Anomaly Detection

arXiv:2605.15062v1 Announce Type: new Abstract: Background. RGB-trained capsule-endoscopy classifiers underperform on small-vessel vascular findings by conflating hemoglobin contrast with bile and ill

Concurrency without Model Changes: Future-based Asynchronous Function Calling for LLMs

arXiv:2605.15077v1 Announce Type: cross Abstract: Function calling, also known as tool use, is a core capability of modern LLM agents but is typically constrained by synchronous execution semantics. U

agentsarxiv-cs-ai

Conditional Attribute Estimation with Autoregressive Sequence Models

arXiv:2605.14004v1 Announce Type: new Abstract: Generative models are often trained with a next-token prediction objective, yet many downstream applications require the ability to estimate or control

local-aiarxiv-cs-ai

Confidence Estimation for LLMs in Multi-turn Interactions

arXiv:2601.02179v2 Announce Type: replace Abstract: While confidence estimation is a promising direction for mitigating hallucinations in Large Language Models (LLMs), current research overwhelmingly

researcharxiv-cs-cl

Conformal Prediction for Multimodal Regression

arXiv:2410.19653v3 Announce Type: replace Abstract: This paper introduces multimodal conformal regression. Traditionally confined to scenarios with solely numerical input features, conformal predictio

researcharxiv-cs-lg

Conformal Thinking: Risk Control for Reasoning on a Compute Budget

arXiv:2602.03814v2 Announce Type: replace Abstract: Reasoning Large Language Models (LLMs) enable test-time scaling, with dataset-level accuracy improving as the token budget increases, motivating ada

Consciousness as Uncommon Self-Knowledge: A Synergistic Information Framework

arXiv:2605.13884v1 Announce Type: cross Abstract: We propose uncommon self-knowledge (USK) as a candidate criterion for consciousness: synergistic information a system carries about itself that exists

Contestable Multi-Agent Debate with Arena-based Argumentative Computation for Multimedia Verification

arXiv:2605.14495v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent fr

agentsarxiv-cs-ai

ContextFlow: Context-Aware Flow Matching For Trajectory Inference From Spatial Omics Data

arXiv:2510.02952v3 Announce Type: replace Abstract: Inferring trajectories from longitudinal spatially-resolved omics data is fundamental to understanding the dynamics of structural and functional tis

local-aiarxiv-cs-lg

Contrastive Multi-Modal Hypergraph Reasoning for 3D Crowd Mesh Recovery

arXiv:2605.13854v1 Announce Type: new Abstract: Multi-person 3D reconstruction is pivotal for real-world interaction analysis, yet remains challenging due to severe occlusions and depth ambiguity. Cur

applicationsarxiv-cs-cv

Conversion of Lexicon-Grammar tables to LMF. Application to French

arXiv:2605.14816v1 Announce Type: new Abstract: We describe the first experiment of conversion of Lexicon-Grammar tables for French verbs into the Lexical Markup Framework (LMF) format. The Lexicon-Gr

researcharxiv-cs-cl

Tools

Cool billboard @FireworksAI_HQ

Fireworks AI posted about a billboard at their headquarters, likely showcasing their company branding, a product announcement, or marketing campaign. The post appears to be promotional content shared

toolsfireworks-ai--x

CoralLite: {mu}CT Reconstruction of Coral Colonies from Individual Corallites

arXiv:2605.15093v1 Announce Type: new Abstract: The life history of an individual coral is archived within the accreting skeleton of the colony. While reef-forming coral colonies (e.g. massive Porites

CoRDS: Coreset-based Representative and Diverse Selection for Streaming Video Understanding

arXiv:2605.14310v1 Announce Type: new Abstract: Streaming video understanding with large vision-language models (VLMs) requires a compact memory that can support future reasoning over an ever-growing

CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers

arXiv:2605.14191v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) deliver remarkable image and video generation quality but incur high computational cost, limiting scalability and on-devic

local-aiarxiv-cs-cv

COREKG: Coreset-Guided Personalized Summarization of Knowledge Graphs

arXiv:2605.14900v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are extensively used across different domains and in several applications. Often, these KGs are very large in size. Such KGs beco

Correctness-Aware Repository Filtering Under Maximum Effective Context Window Constraints

arXiv:2605.14362v1 Announce Type: cross Abstract: Context window efficiency is a practical constraint in large language model (LLM)-based developer tools. Paulsen [12] shows that all tested models deg

COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion

arXiv:2605.15016v1 Announce Type: cross Abstract: As large language models empower healthcare, intelligent clinical decision support has developed rapidly. Longitudinal electronic health records (EHR)

agentsarxiv-cs-ai

CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmarking of Large Language Models in Mental Health Question Answering

model-releasesarxiv-cs-cl

arXiv:2506.08584v4 Announce Type: replace Abstract: Medical question answering (QA) benchmarks often focus on multiple-choice or fact-based tasks, leaving open-ended answers to real patient questions

Covariance-aware sampling for Diffusion Models

arXiv:2605.13910v1 Announce Type: cross Abstract: We present a covariance-aware sampler that improves the quality of pixel-space Diffusion Model (DM) sampling in the few-step regime. We hypothesize th

CRANE: Constrained Reasoning Injection for Code Agents via Nullspace Editing

arXiv:2605.14084v1 Announce Type: cross Abstract: Code agents must both reason over long-horizon repository state and obey strict tool-use protocols. In paired Instruct/Thinking checkpoints, these cap

cred to @thatguybg, playing with micro yesterday inspired this (consider this my feature wish list)

This post shares feature requests and ideas inspired by experimentation with micro (likely a small language model or tool), credited to another developer. It appears to be a wishlist of desired capabi

agentsyohei-nakajima--x

CreFlow: Corrective Reflow for Sparse-Reward Embodied Video Diffusion RL

arXiv:2605.14274v1 Announce Type: new Abstract: Video generation models trained on heterogeneous data with likelihood-surrogate objectives can produce visually plausible rollouts that violate physical

Critic-Driven Voronoi-Quantization for Distilling Deep RL Policies to Explainable Models

arXiv:2605.14897v1 Announce Type: cross Abstract: Despite many successful attempts at explaining Deep Reinforcement Learning policies using distillation, it remains difficult to balance the performanc

Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review

arXiv:2504.18544v3 Announce Type: replace-cross Abstract: Generating synthetic tabular health data is challenging, and evaluating their quality is equally, if not more, complex. This systematic review

Industry

Critique of the 𝕏 algorithm is welcome. There will be monthly updates of the latest algorithm to GitHub with release notes. As reminder, yo…

Critique of the 𝕏 algorithm is welcome. There will be monthly updates of the latest algorithm to GitHub with release notes. As reminder, you can always choose no algorithm via the Following tab. This

industryelon-musk--x

Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets

arXiv:2605.15079v1 Announce Type: new Abstract: Croissant has emerged as the metadata standard for machine learning datasets, providing a structured, JSON-LD-based format that makes dataset discovery,

researcharxiv-cs-lg

Cross-Domain Few-Shot Segmentation via Ordinary Differential Equations over Time Intervals

arXiv:2509.01299v2 Announce Type: replace Abstract: Cross-domain few-shot segmentation (CD-FSS) aims to segment unseen categories with very limited samples while alleviating the negative effects of do

applicationsarxiv-cs-cv

Cross-Linguistic Transcription and Phonological Representation in the Huitongguanxi Huayiyiyu

arXiv:2605.14480v1 Announce Type: new Abstract: Purpose: This study investigates the transcription principles underlying Huitongguanxi Huayiyiyu (HHY), a series of multilingual glossaries compiled by

researcharxiv-cs-cl

Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement

arXiv:2605.14759v1 Announce Type: new Abstract: De novo crystal generation seeks to discover materials that are not merely realistic, but also stable and novel. However, most existing generative model

researcharxiv-cs-lg

CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation

arXiv:2605.14344v1 Announce Type: new Abstract: Generative modeling has emerged as a promising approach for crystal structure discovery. However, existing LLM-based generative models struggle with low

CSI-JEPA: Towards Foundation Representations for Ubiquitous Sensing with Minimal Supervision

arXiv:2605.14171v1 Announce Type: new Abstract: Channel state information (CSI) provides a widely available sensing modality for human and environment perception, but existing CSI sensing models usual

applicationsarxiv-cs-lg

CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications

arXiv:2602.17949v2 Announce Type: replace-cross Abstract: Background: Clinical named entity recognition tools commonly map free text to Unified Medical Language System (UMLS) Concept Unique Identifier

CurveBench: A Benchmark for Exact Topological Reasoning over Nested Jordan Curves

model-releasesarxiv-cs-cv

arXiv:2605.14068v1 Announce Type: new Abstract: We introduce CurveBench, a benchmark for hierarchical topological reasoning from visual input. CurveBench consists of extbf{756 images} of pairwise non-

CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG

arXiv:2605.11611v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for training agentic retrieval-augmented generation (RAG)

D2-CDIG: Controlled Diffusion Remote Sensing Image Generation with Dual Priors of DEM and Cloud-Fog

arXiv:2605.14326v1 Announce Type: new Abstract: Remote sensing image generation provides a reliable data foundation for remote sensing large models and downstream tasks. However, existing controllable

DAPL: Integration of Positive and Negative Descriptions in Text-Based Person Search

arXiv:2405.07459v3 Announce Type: replace Abstract: Text-based person search (TBPS) aims to retrieve specific images of individuals from large datasets using textual descriptions. Existing TBPS method

safetyarxiv-cs-cv

Darwin Family: MRI-Trust-Weighted Evolutionary Merging for Training-Free Scaling of Language-Model Reasoning

arXiv:2605.14386v1 Announce Type: cross Abstract: We present Darwin Family, a framework for training-free evolutionary merging of large language models via gradient-free weight-space recombination. We

Data-Augmented Game Starts for Accelerating Self-Play Exploration in Imperfect Information Games

arXiv:2605.14379v1 Announce Type: cross Abstract: Finding approximate equilibria for large-scale imperfect-information competitive games such as StarCraft, Dota, and CounterStrike remains computationa