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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

Content type

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Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data

DGX agent

arXiv:2605.10129v1 Announce Type: new Abstract: Large language models (LLMs) rely on web-scale corpora for pre-training. The noise inherent in these datasets tends to obscure meaningful patterns and u

model-releasesarxiv-cs-cl

12 May 2026

TabPFN-3 just released: a pre-trained tabular foundation model for up to 1M rows [R][N]

model-releasesr-machinelearning

TabPFN-3 is a pre-trained tabular foundation model that supports datasets up to 1,000,000 rows × 200 features , representing a significant scaling improvement for the TabPFN family. The model delivers

Tabular Foundation Model for Generative Modelling

model-releasesarxiv-cs-lg

arXiv:2605.09424v1 Announce Type: new Abstract: Generative modelling is a demanding test of foundation models, because it requires robust, holistic representation learning for a given data modality, r

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

model-releasesarxiv-cs-cl

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

TAD: Temporal-Aware Trajectory Self-Distillation for Fast and Accurate Diffusion LLM

arXiv:2605.09536v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising paradigm for parallel text generation, but in practice they face an accuracy-parallelism tra

researcharxiv-cs-ai

TAH-QUANT: Effective Activation Quantization in Pipeline Parallelism over Slow Network

arXiv:2506.01352v2 Announce Type: replace Abstract: Decentralized training of large language models offers the opportunity to pool computational resources across geographically distributed participant

Talk to Your Slides: High-Efficiency Slide Editing via Language-Driven Structured Data Manipulation

model-releasesarxiv-cs-cl

arXiv:2505.11604v5 Announce Type: replace Abstract: Editing presentation slides is a frequent yet tedious task, ranging from creative layout design to repetitive text maintenance. While recent GUI-bas

Industry

Talked to a friend at a top AI lab. Their whole team is former journalists, training models on poems, summaries, and creative writing. I use…

industryallie-k--miller--x

Talked to a friend at a top AI lab. Their whole team is former journalists, training models on poems, summaries, and creative writing. I use AI every day and can see that it tends to flatten my writin

Targeted Synthetic Control Method

arXiv:2602.04611v2 Announce Type: replace-cross Abstract: The synthetic control method (SCM) estimates causal effects in panel data with a single-treated unit by constructing a counterfactual outcome

safetyarxiv-cs-lg

TARO: Temporal Adversarial Rectification Optimization Using Diffusion Models as Purifiers

arXiv:2605.08440v1 Announce Type: cross Abstract: Adversarial purification with diffusion models seeks to project adversarial examples back toward the data manifold, but balancing semantic preservatio

researcharxiv-cs-cv

Task-Agnostic Noisy Label Detection via Standardized Loss Aggregation

arXiv:2605.10165v1 Announce Type: cross Abstract: Noisy labels are common in large-scale medical imaging datasets due to inter-observer variability and ambiguous cases. We propose a statistically grou

researcharxiv-cs-ai

Task-Aware Calibration: Provably Optimal Decoding in LLMs

arXiv:2605.10202v1 Announce Type: cross Abstract: LLM decoding often relies on the model's predictive distribution to generate an output. Consequently, misalignment with respect to the true generating

Task complexity shapes internal representations and robustness in neural networks

arXiv:2508.05463v2 Announce Type: replace-cross Abstract: Neural networks excel across a wide range of tasks, yet remain black boxes. In particular, how their internal representations are shaped by th

researcharxiv-cs-ai

TD3B: Transition-Directed Discrete Diffusion for Allosteric Binder Generation

arXiv:2605.09810v1 Announce Type: cross Abstract: Protein function is often controlled by ligands that bias the direction of state transitions, such as agonists and antagonists, rather than stabilizin

safetyarxiv-cs-lg

Local Ai

Teacher-Aware Evolution of Heuristic Programs from Learned Optimization Policies

arXiv:2605.10634v1 Announce Type: new Abstract: LLM-based automatic heuristic design has shown promise for generating executable heuristics for combinatorial optimization, but existing methods mainly

local-aiarxiv-cs-ai

Teaching LLMs to See Graphs: Unifying Text and Structural Reasoning

model-releasesarxiv-cs-lg

arXiv:2605.10247v1 Announce Type: new Abstract: Using Large Language Models (LLMs) to process graph-structured data is an active research area, yet current state-of-the-art approaches typically rely o

Tutorials

Teaching Molecular Dynamics to a Non-Autoregressive Ionic Transport Predictor

arXiv:2605.09311v1 Announce Type: cross Abstract: Unlike most static material properties widely studied in the machine learning literature, ionic transport properties are inherently dynamic, making th

tutorialsarxiv-cs-ai

Team-Based Self-Play With Dual Adaptive Weighting for Fine-Tuning LLMs

arXiv:2605.09922v1 Announce Type: cross Abstract: While recent self-training approaches have reduced reliance on human-labeled data for aligning LLMs, they still face critical limitations: (i) sensiti

TeleResilienceBench: Quantifying Resilience for LLM Reasoning in Telecommunications

model-releasesarxiv-cs-lg

arXiv:2605.09929v1 Announce Type: new Abstract: Deploying large language models in telecommunications requires more than task accuracy. In realistic workflows, a model may inherit partially completed

'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

Temperature and Persona Shape LLM Agent Consensus With Minimal Accuracy Gains in Qualitative Coding

arXiv:2507.11198v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) enable new possibilities for qualitative research at scale, including annotation and qualitative coding of educat

agentsarxiv-cs-ai

Temporal-Decay Shapley: A Time-Aware Data Valuation Framework for Time-Series Data

arXiv:2605.08153v1 Announce Type: new Abstract: With the rapid development of machine learning applications on time-series data, accurately assessing the value of training samples has become essential

Temporal Sampling Frequency Matters: A Capacity-Aware Study of End-to-End Driving Trajectory Prediction

arXiv:2605.10388v1 Announce Type: new Abstract: End to end (E2E) autonomous driving trajectory prediction is often trained with camera frames sampled at the highest available temporal frequency, assum

agentsarxiv-cs-cv

Applications

Temporal Tokenization Strategies for Event Sequence Modeling with Large Language Models

arXiv:2512.13618v3 Announce Type: replace Abstract: Representing continuous time is a critical and under-explored challenge in modeling temporal event sequences with large language models (LLMs). Vari

applicationsarxiv-cs-cl

Tensor Product Representation Probes Reveal Shared Structure Across Linear Directions

arXiv:2605.09967v1 Announce Type: new Abstract: While researchers are finding concepts represented as linear directions in language models, a bag of linear directions fails to capture relational struc

Tutorials

Terminal Matters: Kinodynamic Planning with a Terminal Cost and Learned Uncertainty in Belief State-Cost Space

arXiv:2605.09046v1 Announce Type: new Abstract: In many real-world robotic tasks, robots must generate dynamically feasible motions that reliably reach desired goals even under uncertainty. Yet existi

tutorialsarxiv-cs-ro

Test-Time Speculation

model-releasesarxiv-cs-cl

arXiv:2605.09329v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference by using a fast draft model to generate tokens and a more accurate target model to verify them. Its perfo

Test-Time Training for Visual Foresight Vision-Language-Action Models

arXiv:2605.08215v1 Announce Type: new Abstract: Visual Foresight VLA (VF-VLA) has become a prominent architectural choice in the recent VLA due to its impressive performance. Nevertheless, the inheren

researcharxiv-cs-cv

Text-Guided Multi-Scale Frequency Representation Adaptation

arXiv:2605.08181v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning methods introduce a small number of training parameters, enabling pre-trained models to adapt rapidly to new data dist

Tutorials

TextBridgeGNN: Pre-training Graph Neural Network for Cross-Domain Recommendation via Text-Guided Transfer

arXiv:2601.02366v2 Announce Type: replace-cross Abstract: Graph-based recommendation has achieved great success in recent years. The classical graph recommendation model utilizes ID embedding to store

tutorialsarxiv-cs-ai

TFM-Retouche: A Lightweight Input-Space Adapter for Tabular Foundation Models

arXiv:2605.06047v2 Announce Type: replace-cross Abstract: Tabular foundation models (TFMs), such as TabPFN-2.6, TabICLv2, ConTextTab, Mitra, LimiX, and TabDPT, achieve strong zero-shot performance thr

Thanks to everyone who showcased their projects in today's Hermes Agent Jam!

Nous Research held a 'Hermes Agent Jam' event where developers showcased projects built using or related to their Hermes agent framework. The event appears to have been a community-driven showcase hig

agentsnous-research--x

Local Ai

Thanks to the @huggingface team for adding Hermes Agent to local apps and shipping a native Hermes traces viewer!

Thanks to the @huggingface team for adding Hermes Agent to local apps and shipping a native Hermes traces viewer! 🆕 Hugging Face 🤝 Hermes Agent 🔥 > we added Hermes Agent to local apps: run it locally

local-ainous-research--x

Industry

The 9 biggest new features in Android 17

Would it shock you to hear that Android 17 is filled with new AI-enabled features, like improved dictation and vibe-coded widgets? Fortunately, that's not all. The platform is getting non-AI updates t

industrythe-verge-ai

The Accountability Paradox: How Platform API Restrictions Undermine AI Transparency Mandates

arXiv:2505.11577v4 Announce Type: replace-cross Abstract: Recent application programming interface (API) restrictions on major social media platforms challenge compliance with the EU Digital Services

The agent also reimplemented the “Blues Improvisation” experiment by @douglas_eck and @SchmidhuberAI in 2002 which show that LSTMs can learn…

The agent also reimplemented the “Blues Improvisation” experiment by @douglas_eck and @SchmidhuberAI in 2002 which show that LSTMs can learn temporal structure in music. Finding temporal structure in

agentsdavid-ha--x

The Agent Use of Agent Beings: Agent Cybernetics Is the Missing Science of Foundation Agents

arXiv:2605.10754v1 Announce Type: new Abstract: LLM-based foundation agents that perceive, reason, and act across thousands of reasoning steps are rapidly becoming the dominant paradigm for deploying

agentsarxiv-cs-ai

The Alpha Blending Hypothesis: Compositing Shortcut in Deepfake Detection

model-releasesarxiv-cs-cv

arXiv:2605.10334v1 Announce Type: new Abstract: Recent deepfake detection methods demonstrate improved cross-dataset generalization, yet the underlying mechanisms remain underexplored. We introduce th

The Art of the Jailbreak: Formulating Jailbreak Attacks for LLM Security Beyond Binary Scoring

arXiv:2605.09225v1 Announce Type: cross Abstract: Jailbreak attacks -- adversarial prompts that bypass LLM alignment through purely linguistic manipulation -- pose a growing operational security threa

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 Astonishing Ability of Large Language Models to Parse Jabberwockified Language

arXiv:2602.23928v2 Announce Type: replace Abstract: We show that large language models (LLMs) have an astonishing ability to recover meaning from severely degraded English texts. Texts in which conten

The Attacker in the Mirror: Breaking Self-Consistency in Safety via Anchored Bipolicy Self-Play

arXiv:2605.08427v1 Announce Type: new Abstract: Self-play red team is an established approach to improving AI safety in which different instances of the same model play attacker and defender roles in

The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT nicode{x2013} Multitracer Multicenter Generalization

arXiv:2605.05775v2 Announce Type: replace-cross Abstract: We report the design and results of the third autoPET challenge (MICCAI 2024), which benchmarked automated lesion segmentation in whole-body P

Hardware

The benchmarks show the gap. NVLS all-reduce latency drops from 586.1µs on H200 to 313.3µs on GB200. In MoE prefill at EP=4, combine falls f…

The benchmarks show the gap. NVLS all-reduce latency drops from 586.1µs on H200 to 313.3µs on GB200. In MoE prefill at EP=4, combine falls from 730.1µs to 438.5µs. For decode, GB200 sustains much high

hardwareperplexity--x

The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently

arXiv:2605.10237v1 Announce Type: new Abstract: We study how temporal correlations in the data can make certain sparse learning problems efficiently learnable by gradient-based methods. Our focus is o

The Bystander Effect in Multi-Agent Reasoning: Quantifying Cognitive Loafing in Collaborative Interactions

arXiv:2605.10698v1 Announce Type: cross Abstract: Multi-agent systems (MAS) assume that collaborating inherently improves Large Language Model (LLM) reasoning. We challenge this by demonstrating that