Search: “model-releases”

RE-VLM: Event-Augmented Vision-Language Model for Scene Understanding

arXiv:2605.19329v1 Announce Type: cross Abstract: Conventional vision-language models (VLMs) struggle to interpret scenes captured under adverse conditions (e.g., low light, high dynamic range, or fas

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

ReacTOD: Bounded Neuro-Symbolic Agentic NLU for Zero-Shot Dialogue State Tracking

DGX agent

arXiv:2605.19077v1 Announce Type: cross Abstract: Task-oriented dialogue systems -- handling transactions, reservations, and service requests -- require predictable behavior, yet the moderately-sized

model-releasesarxiv-cs-ai

20 May 2026

Real-World On-Vehicle Evaluation of Embedding-Based Anomaly Detection

arXiv:2605.19744v1 Announce Type: new Abstract: Detecting anomalies in traffic scenes is crucial for ensuring safety in autonomous driving, yet collecting representative anomalous data remains challen

Rebalancing Reference Frame Dominance to Improve Motion in Image-to-Video Models

arXiv:2605.19398v1 Announce Type: cross Abstract: Image-to-video models often generate videos that remain overly static, compared to text-to-video models. While prior approaches mitigate this issue by

RECIPE: Procedural Planning via Grounding in Instructional Video

arXiv:2605.19976v1 Announce Type: new Abstract: Visual planning asks a model to generate the remaining steps of a procedure in natural language given a partial video context and a goal. Progress on th

RecoAtlas: From Semantic Plausibility to Set-Level Utility in LLM Recommendation Agents

arXiv:2605.18805v1 Announce Type: cross Abstract: LLM recommendation agents increasingly produce structured recommendation reports: sets of items accompanied by natural-language justifications. Yet ex

Recursive Entropic Risk Optimization in Discounted MDPs: Sample Complexity Bounds with a Generative Model

arXiv:2506.00286v3 Announce Type: replace-cross Abstract: We study risk-sensitive reinforcement learning in finite discounted MDPs with recursive entropic risk measures (ERM), where the risk parameter

Replacement Learning: Training Neural Networks with Fewer Parameters

arXiv:2605.19533v1 Announce Type: new Abstract: End-to-end training with full-depth backpropagation remains the dominant paradigm for optimizing deep neural networks, but its efficiency deteriorates a

Reporting from Google I/O 2026 with the four biggest themes from one of the biggest AI labs in the world. 🎤 Voice AI as an interface Google…

model-releasesallie-k--miller--x

Reporting from Google I/O 2026 with the four biggest themes from one of the biggest AI labs in the world. 🎤 Voice AI as an interface Google and Samsung announced new Gemini-powered glasses with Gentle

Resilient Byzantine Agreement with Predictions

arXiv:2605.19452v1 Announce Type: cross Abstract: This paper studies the Byzantine Agreement problem where the nodes have access to a predictor that flags nodes for suspicion of faulty (Byzantine) beh

Rethinking How to Remember: Beyond Atomic Facts in Lifelong LLM Agent Memory

arXiv:2605.19952v1 Announce Type: new Abstract: To enable reliable long-term interaction, LLM agents require a memory system that can faithfully store, efficiently retrieve, and deeply reason over acc

Retrieval-Augmented Generation for Natural Language Processing: A Survey

arXiv:2407.13193v4 Announce Type: replace Abstract: Large language models (LLMs) have achieved strong empirical performance in various fields, benefiting from their huge amount of parameters that stor

Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model Behavior

arXiv:2510.14261v2 Announce Type: replace Abstract: We present an experimental recipe for studying the relationship between training data and language model (LM) behavior. We outline steps for interve

RoboJailBench: Benchmarking Adversarial Attacks and Defenses in Embodied Robotic Agents

model-releasesarxiv-cs-ro

arXiv:2605.19328v1 Announce Type: cross Abstract: Recent advances in Vision-Language Models (VLMs) facilitate a new class of embodied AI systems, where these models are integrated into physical platfo

Robots that learn to evaluate models of collective behavior

model-releasesarxiv-cs-ro

arXiv:2604.07303v2 Announce Type: replace Abstract: Understanding and modeling animal behavior is essential for studying collective motion, decision-making, and bio-inspired robotics. Yet, evaluating

Robust Basis Spline Decoupling for the Compression of Transformer Models

arXiv:2605.18794v1 Announce Type: cross Abstract: Decoupling is a powerful modeling paradigm for representing multivariate functions as compositions of linear transformations and univariate nonlinear

SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction

arXiv:2605.19014v1 Announce Type: new Abstract: Microsimulation models used by ministries of finance and central banks rely on parametric processes for lifetime earnings that capture only first and se

ScheduleFree+: Scaling Learning-Rate-Free & Schedule-Free Learning to Large Language Models

arXiv:2605.19095v1 Announce Type: cross Abstract: Schedule-Free Learning has shown promise as a practical anytime training method for machine learning, showing success across dozens of standard benchm

SciCustom: A Framework for Custom Evaluation of Scientific Capabilities in Large Language Models

arXiv:2605.19357v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to scientific research, yet existing evaluations often fail to reflect the fine-grained capabiliti

Search Self-play: Pushing the Frontier of Agent Capability without Supervision

arXiv:2510.18821v3 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has become the mainstream technique for training LLM agents. However, RLVR highly depends on w

Self-Filtered Distillation with LLMs-generated Trust Indicators for Reliable Patent Classification

arXiv:2510.05431v4 Announce Type: replace Abstract: Organizing large-scale patent corpora according to classification schemes is a core information management task that determines the accuracy and eff

Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post o…

Self-improving AI is a big deal! As a first step, I've been exploring how much of the post-training can be automated. Here is a first post on how I am using @FireworksAI_HQ Agent to automate LLM fine-

model-releasesdair-ai--x

Semantic-Enriched Latent Visual Reasoning

arXiv:2605.19342v1 Announce Type: new Abstract: Multimodal latent-space reasoning aims to replace explicit thinking with images by performing visual reasoning directly in a compact latent space. Howev

Sequential Consensus for Multi-Agent LLM Debates: A Wald-SPRT compute governor with calibration-based failure detection

arXiv:2605.19193v1 Announce Type: new Abstract: Multi-agent LLM debate improves factuality and reasoning, but most recipes pick a fixed round count, over-spending on easy items and under-spending on h

Sharper Bounds for Chebyshev Moment Matching, with Applications

arXiv:2408.12385v3 Announce Type: replace-cross Abstract: We study the problem of approximately recovering a probability distribution given noisy measurements of its Chebyshev polynomial moments. This

Simply Stabilizing the Loop via Fully Looped Transformer

arXiv:2605.18797v1 Announce Type: cross Abstract: Scaling model performance typically requires increasing model size. Looped Transformer offers a compelling alternative by iteratively reusing the same

SLoW: Select Low-frequency Words! Automatic Dictionary Selection for Translation on Large Language Models

arXiv:2507.18902v2 Announce Type: replace Abstract: There are more than 7,000 languages around the world, and current Large Language Models (LLMs) only support hundreds of languages. Dictionary-based

Smooth Piecewise Cutting for Neural Operator to Handle Discontinuities and Sharp Transitions

arXiv:2605.19823v1 Announce Type: cross Abstract: Neural operators have achieved strong performance in learning solution operators of partial differential equations (PDEs), but their inherently contin

Sonar-TS: Search-Then-Verify Natural Language Querying for Time Series Databases

arXiv:2602.17001v2 Announce Type: replace Abstract: Natural Language Querying for Time Series Databases (NLQ4TSDB) aims to assist non-expert users retrieve meaningful events, intervals, and summaries

SpecX: A Large-Scale Benchmark for Multi-Modal Spectroscopy and Cross-Paradigm Evaluation

arXiv:2605.18791v1 Announce Type: cross Abstract: Existing spectral benchmarks are limited in scale, modality alignment, and evaluation scope, and typically focus on either specialized models or multi

STAR-PolyaMath: Multi-Agent Reasoning under Persistent Meta-Strategic Supervision

arXiv:2605.19338v1 Announce Type: cross Abstract: Frontier AI models and multi-agent systems have led to significant improvements in mathematical reasoning. However, for problems requiring extended, l

STAR: Semantic-Tuned and Tail-Adaptive Retriever for Graph-Augmented Generation

arXiv:2605.18765v1 Announce Type: cross Abstract: To augment Large Language Models (LLMs) for multi-hop question answering, a mainstream solution within Graph Retrieval Augmented Generation (GraphRAG)

Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space

arXiv:2602.18718v2 Announce Type: replace-cross Abstract: For approximating a target distribution given only its unnormalized log-density, stochastic gradient-based variational inference (VI) algorith

Streamlined Constraint Reasoning via CNN Pattern Recognition on Enumerated Solutions

arXiv:2605.19895v1 Announce Type: new Abstract: Constraint programming practitioners accelerate hard problems through a layered set of techniques applied in order of risk. Standard hardening (symmetry

Structured Layout Priors for Robust Out-of-Distribution Visual Document Understanding

arXiv:2605.19866v1 Announce Type: new Abstract: Vision-Language Models (VLMs) parse documents end-to-end but frequently break down on layouts unlike those seen in training. We attribute this to a two-

Subagents running locally and simultaneously on MacBook Pro M5 with Codex CLI + @lmstudio to review code and find bugs using Qwen 3.6 Powere…

model-releaseslm-studio--x

Subagents running locally and simultaneously on MacBook Pro M5 with Codex CLI + @lmstudio to review code and find bugs using Qwen 3.6 Powered by the updated MLX engine with batching in beta in the app

SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation

arXiv:2605.18920v1 Announce Type: cross Abstract: Generative Recommendation (GR) has emerged as a promising paradigm by formulating item recommendation as a sequence-to-sequence generation task over i

Synthesis and Evaluation of Long-term History-aware Medical Dialogue

arXiv:2605.19766v1 Announce Type: cross Abstract: An effective healthcare agent must be able to recall and reason over a patient's longitudinal medical history. However, the absence of datasets with r

Synthetic Data Generation for Brain-Computer Interfaces: Overview, Benchmarking, and Future Directions

arXiv:2603.12296v2 Announce Type: replace-cross Abstract: Deep learning has achieved transformative performance across diverse domains, largely driven by large-scale and high-quality training data. In

TADA! Tuning Audio Diffusion Models through Activation Steering

arXiv:2602.11910v2 Announce Type: replace-cross Abstract: Audio diffusion models can synthesize high-fidelity music from text, yet achieving fine-grained control over specific musical attributes remai

Tail Annealing for Heavy-Tailed Flow Matching

arXiv:2605.20068v1 Announce Type: cross Abstract: Standard generative models struggle with heavy-tailed data: Lipschitz architectures cannot produce power-law tails from Gaussian noise, and interpolat

Taming the Thinker: Conditional Entropy Shaping for Adaptive LLM Reasoning

arXiv:2605.19358v1 Announce Type: new Abstract: Entropy-based deep reasoning has emerged as a promising direction for improving the reasoning capabilities of Large Language Models (LLMs), but existing

Target-Aligned Reinforcement Learning

arXiv:2603.29501v2 Announce Type: replace-cross Abstract: Many value-based deep reinforcement learning algorithms rely on target networks - lagged copies of the online network - to stabilize training.

Targeted Downstream-Agnostic Attack

arXiv:2605.19446v1 Announce Type: cross Abstract: Recently, pre-trained encoders have gained widespread use due to their strong capability in representation extraction. However, they are vulnerable to

TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards

arXiv:2605.19320v1 Announce Type: new Abstract: Faithful text rendering remains a persistent weakness of large text-to-image generative models, as it requires both semantic instruction following and f

The Annotation Scarcity Paradox in Low-Resource NLP Evaluation: A Decade of Acceleration and Emerging Constraints

arXiv:2605.19066v1 Announce Type: new Abstract: Over the past decade, low-resource natural language processing (NLP) has experienced explosive growth, propelled by cross-lingual transfer, massively mu

The Evaluation Game: Beyond Static LLM Benchmarking

arXiv:2605.19377v1 Announce Type: cross Abstract: As jailbreaks, adversarially crafted inputs that bypass safety constraints, continue to be discovered in Large Language Models, practitioners increasi

The frontier is still jagged though (here is Gemini 3.5 Flash messing up counting letters in words) https://x.com/RRiscio37389/status/205719…

model-releasesethan-mollick--x

The frontier is still jagged though (here is Gemini 3.5 Flash messing up counting letters in words) https://x.com/RRiscio37389/status/2057193260745883962?s=20 @emollick Proof: https://gemini.google.co