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arXiv:2605.10913v1 Announce Type: new Abstract: We introduce Shepherd, a functional programming model that formalizes meta-agent operations on target agents as functions, with core operations mechaniz

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Research

ShifaMind: A Multiplicative Concept Bottleneck for Interpretable ICD-10 Coding

DGX agent

arXiv:2605.08482v1 Announce Type: cross Abstract: Automated ICD-10 coding from clinical discharge summaries requires models that are both accurate on long-tailed multi-label classification tasks and i

researcharxiv-cs-cl

12 May 2026

SimReg: Achieving Higher Performance in the Pretraining via Embedding Similarity Regularization

arXiv:2605.08809v1 Announce Type: cross Abstract: Pretraining large language models (LLMs) with next-token prediction has led to remarkable advances, yet the context-dependent nature of token embeddin

researcharxiv-cs-ai

Single-Thread JPEG Decoder Benchmarks Mis-Evaluate ML Data Loaders

arXiv:2605.08731v1 Announce Type: cross Abstract: JPEG decode is routine ML infrastructure, but Python decoder choices are often justified by single-process, single-thread microbenchmarks. We audit th

Sinkhorn Treatment Effects: A Causal Optimal Transport Measure

arXiv:2605.08485v1 Announce Type: cross Abstract: We introduce the Sinkhorn treatment effect, an entropic optimal transport measure of divergence between counterfactual distributions. Unlike classical

SLASH the Sink: Sharpening Structural Attention Inside LLMs

arXiv:2605.10503v1 Announce Type: new Abstract: Large Language Models (LLMs) show remarkable semantic understanding but often struggle with structural understanding when processing graph topologies in

SpaceMind++: Toward Allocentric Cognitive Maps for Spatially Grounded Video MLLMs

arXiv:2605.09449v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have made remarkable progress in visual understanding and language-based reasoning, yet they lack a pers

researcharxiv-cs-cv

SpaceX is officially my fav art account now

model-releaseselon-musk--x

SpaceX's official social media account is being praised for its engaging visual content and aesthetic presentation, earning recognition as a favorite among followers for its artistic approach to shari

Spectrally-Guided Diffusion Noise Schedules

arXiv:2603.19222v2 Announce Type: replace Abstract: Denoising diffusion models are widely used for high-quality image and video generation. Their performance depends on noise schedules, which define t

researcharxiv-cs-cv

Spherical Flows for Sampling Categorical Data

arXiv:2605.05629v2 Announce Type: replace-cross Abstract: We study the problem of learning generative models for discrete sequences in a continuous embedding space. Whereas prior approaches typically

SSA: Improving Performance With a Better Scoring Function

arXiv:2508.14685v4 Announce Type: replace Abstract: While transformer models exhibit strong in-context learning (ICL) abilities, they often fail to generalize under simple distribution shifts. We anal

Structure-Preserving Reconstruction of Convex Lipschitz Functionals on Hilbert Spaces from Finite Samples

arXiv:2605.08559v1 Announce Type: cross Abstract: Convex functionals are ubiquitous in applied analysis, appearing as value functions, risk measures, super-hedging prices, and loss functionals in mach

Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review

arXiv:2605.08963v1 Announce Type: cross Abstract: Machine Learning (ML) models trained on complex health surveys such as the National Health and Nutrition Examination Survey (NHANES) often ignore prim

safetyarxiv-cs-lg

SynerMedGen: Synergizing Medical Multimodal Understanding with Generation via Task Alignment

arXiv:2605.08724v1 Announce Type: new Abstract: Unifying multimodal understanding and generation is a compelling frontier that is beginning to emerge in the medical field. However, the limited existin

safetyarxiv-cs-cv

TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems

arXiv:2605.09539v1 Announce Type: new Abstract: Multi-agent systems (MAS) have emerged as a promising paradigm for solving complex tasks. Recent work has explored self-evolving MAS that automatically

'tell me about recent funding and news for openai and anthropic' result with @wokeloai mcp included today's trial, tomoro acquisition, and c…

model-releasesyohei-nakajima--x

Yohei Nakajima shared recent funding and news updates about OpenAI and Anthropic on X, including information about a trial involving the wokeloai MCP, a tomorrow acquisition, and additional details (c

TELL-TALE: Task Efficient LLMs with Task Aware Layer Elimination

arXiv:2510.22767v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) typically come with a fixed architecture, despite growing evidence that not all layers contribute equally to ever

The Association of Transformer-based Sentiment Analysis with Symptom Distress and Deterioration in Routine Psychotherapy Care

arXiv:2605.09838v1 Announce Type: new Abstract: Sentiment analysis has been of long-standing interest in psychotherapy research. Recently, the Transformer deep learning architecture has produced text-

The Extrapolation Cliff in On-Policy Distillation of Near-Deterministic Structured Outputs

arXiv:2605.08737v1 Announce Type: cross Abstract: On-policy distillation (OPD) is widely used for LLM post-training. When pushed with a reward-extrapolation coefficient lambda > 1, the student can lif

The Trap of Trajectory: Towards Understanding and Mitigating Spurious Correlations in Agentic Memory

arXiv:2605.09330v1 Announce Type: cross Abstract: Agentic memory enables LLMs to persist information beyond a single context window and reuse it in later decisions, but it also introduces a new vulner

The Truth Lies Somewhere in the Middle (of the Generated Tokens)

arXiv:2605.09969v1 Announce Type: cross Abstract: How should hidden states generated autoregressively be collapsed into a representation that reflects a language model's internal state? Despite tokens

local-aiarxiv-cs-cl

The US House Oversight Committee launches a probe into potential conflicts in Sam Altman's personal investments; letter: several GOP AGs call for an SEC review (Wall Street Journal)

Wall Street Journal: The US House Oversight Committee launches a probe into potential conflicts in Sam Altman's personal investments; letter: several GOP AGs call for an SEC review — Republican-led Ho

model-releasestechmeme

The Wristband Gaussian Loss: Deterministic, Composable Latents via a Sphere-Interval Decomposition

arXiv:2605.08749v1 Announce Type: new Abstract: We present the Wristband Gaussian Loss, a deterministic batch loss for Gaussianizing point embeddings without sampling, KL terms, or iterative transport

Tight Generalization Bounds for Noiseless Inverse Optimization

arXiv:2605.08866v1 Announce Type: cross Abstract: Inverse optimization (IO) seeks to infer the parameters of a decision-maker's objective from observed context--action data. We study noiseless IO, whe

TiledAttention: a CUDA Tile SDPA Kernel for PyTorch

arXiv:2603.01960v2 Announce Type: replace-cross Abstract: TiledAttention is a scaled dot-product attention (SDPA) forward operator for SDPA research on NVIDIA GPUs. Implemented in cuTile Python (TileI

TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling

arXiv:2605.09281v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models achieve remarkable performance by sparsely activating specialized experts, yet their massive parameters in experts pose

researcharxiv-cs-lg

Time-Warping Recurrent Neural Networks for Transfer Learning

arXiv:2604.02474v2 Announce Type: replace Abstract: Dynamical systems describe how a physical system evolves over time. Physical processes can evolve faster or slower in different environmental condit

researcharxiv-cs-lg

Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents

arXiv:2605.10832v1 Announce Type: new Abstract: Multimodal deep search requires an agent to solve open-world problems by chaining search, tool use, and visual reasoning over evolving textual and visua

Transformers Provably Learn Sparse XOR with Polylogarithmic Parameters

arXiv:2502.07553v2 Announce Type: replace Abstract: Learning sparse parity functions has become a theoretical testbed for studying feature learning in neural networks. However, existing analyses prima

TTCD:Transformer Integrated Temporal Causal Discovery from Non-Stationary Time Series Data

arXiv:2605.08111v1 Announce Type: cross Abstract: The widespread availability of complex time series data in various domains such as environmental science, epidemiology, and economics demands robust c

Uncertainty-Aware and Decoder-Aligned Learning for Video Summarization

arXiv:2605.09507v1 Announce Type: new Abstract: Video summarization aims to produce a compact representation of a long video by selecting a subset of temporally important segments that best reflect hu

safetyarxiv-cs-cv

UniShield: Unified Face Attack Detection via KG-Informed Multimodal Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.08709v1 Announce Type: new Abstract: Unified face attack detection (UAD) requires recognizing physical spoofing and digital forgery within a shared decision space, yet existing discriminati

Unpredictability dissociates from structured control in language agents

arXiv:2605.09692v1 Announce Type: new Abstract: Unpredictable behavior is often taken as evidence of control, yet stochastic dispersion and structured action control need not coincide. This paper test

v0.30.0-rc15

v0.30.0-rc15 is a release candidate version of Ollama, an open-source platform for running large language models locally. This particular release is part of the development cycle leading toward the st

local-aiollama-releases

Agents

VECTOR-Drive: Tightly Coupled Vision-Language and Trajectory Expert Routing for End-to-End Autonomous Driving

arXiv:2605.08830v1 Announce Type: cross Abstract: End-to-end autonomous driving requires models to understand traffic scenes, infer driving intent, and generate executable motion plans. Recent vision-

agentsarxiv-cs-ai

Tutorials

VeloGauss: Learning Physically Consistent Gaussian Velocity Fields from Videos

arXiv:2605.10567v1 Announce Type: new Abstract: In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without re

tutorialsarxiv-cs-cv

Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward

arXiv:2605.09920v1 Announce Type: cross Abstract: While Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as a promising post-training paradigm for Large Language Models (LLMs

Vocabulary Hijacking in LVLMs: Unveiling Critical Attention Heads by Excluding Inert Tokens to Mitigate Hallucination

arXiv:2605.10622v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal tasks, yet their reliability is persistently undermined by halluc

local-aiarxiv-cs-cv

VORT: Adaptive Power-Law Memory for NLP Transformers

arXiv:2605.08966v1 Announce Type: new Abstract: Standard Transformers impose near-exponential decay on the influence of distant tokens, conflicting with the power-law structure of long-range dependenc

WavesFM: Hierarchical Representation Learning for Longitudinal Wearable Sensor Waveforms

arXiv:2605.09173v1 Announce Type: cross Abstract: Wearable sensors enable the continuous acquisition of high-resolution physiological waveforms, such as photoplethysmography and accelerometry, under f

local-aiarxiv-cs-ai

We integrated FrontierCS into Harbor and are releasing a preview long-horizon agent leaderboard (up to 835 turns, ~200K output tokens) with …

model-releaseskimi-moonshot--x

We integrated FrontierCS into Harbor and are releasing a preview long-horizon agent leaderboard (up to 835 turns, ~200K output tokens) with Kimi K2.6 @Kimi_Moonshot (score 46.9) and Claude Code Opus 4

Applications

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies

arXiv:2605.08289v1 Announce Type: cross Abstract: Multivariate time series forecasting is critical in many real-world systems, and thus modeling cross-channel dependencies is essential. Although exist

applicationsarxiv-cs-ai

When Agents Overtrust Environmental Evidence: An Extensible Agentic Framework for Benchmarking Evidence-Grounding Defects in LLM Agents

arXiv:2605.08828v1 Announce Type: new Abstract: Large language model agents increasingly operate through environment-facing scaffolds that expose files, web pages, APIs, and logs. These observations i

When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning

arXiv:2605.09109v1 Announce Type: new Abstract: Many continuous-control problems ship with a competent but suboptimal controller (a tuned PID, a hand-designed gait). A growing family of methods uses s

When Can Digital Personas Reliably Approximate Human Survey Findings?

arXiv:2605.10659v1 Announce Type: cross Abstract: Digital personas powered by Large Language Models (LLMs) are increasingly proposed as substitutes for human survey respondents, yet it remains unclear

When Does Non-Uniform Replay Matter in Reinforcement Learning?

arXiv:2605.10236v1 Announce Type: cross Abstract: Modern off-policy reinforcement learning algorithms often rely on simple uniform replay sampling and it remains unclear when and why non-uniform repla

Where Does Long-Context Supervision Actually Go? Effective-Context Exposure Balancing

arXiv:2605.10544v1 Announce Type: new Abstract: Long-context adaptation is often viewed as window scaling, but this misses a token-level supervision mismatch: in packed training with document masking,

Why Zeroth-Order Adaptation May Forget Less: A Randomized Shaping Theory

arXiv:2605.10658v1 Announce Type: new Abstract: Continual learning requires new-task adaptation without damaging previously acquired capabilities. Recent forward-pass and zeroth-order (ZO) results sho