Search: “model-releases”

BEExformer: A Fast Inferencing Binarized Transformer with Early Exits

arXiv:2412.05225v3 Announce Type: replace Abstract: Large Language Models (LLMs) based on transformers achieve cutting-edge results on a variety of applications. However, their enormous size and proce

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Model Releases

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training

DGX agent

arXiv:2605.12483v1 Announce Type: new Abstract: In settings where labeled verifiable training data is the binding constraint, each checked example should be allocated carefully. The standard practice

model-releasesarxiv-cs-lg

13 May 2026

Beyond Localization: A Comprehensive Diagnosis of Perspective-Conditioned Spatial Reasoning in MLLMs from Omnidirectional Images

arXiv:2605.12413v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) show strong visual perception, yet remain limited in reasoning about space under changing viewpoints. We study

Beyond Parameter Aggregation: Semantic Consensus for Federated Fine-Tuning of LLMs

arXiv:2605.11857v1 Announce Type: new Abstract: Federated fine-tuning of large language models is commonly formulated as a parameter aggregation problem. However, even parameter-efficient methods requ

Beyond Prediction: Interval Neural Networks for Uncertainty-Aware System Identification

arXiv:2605.11460v1 Announce Type: new Abstract: System identification (SysID) is critical for modeling dynamical systems from experimental data, yet traditional approaches often fail to capture nonlin

Beyond Text Prompts: Visual-to-Visual Generation as A Unified Paradigm

arXiv:2605.12271v1 Announce Type: new Abstract: Humans often specify and create through visual artifacts: typography sheets, sketches, reference images, and annotated scenes. Yet modern visual generat

Bin Latent Transformer (BiLT): A shift-invariant autoencoder for calibration-free spectral unmixing of turbid media

arXiv:2605.11829v1 Announce Type: cross Abstract: The accurate recovery of constituent-level optical properties from integrating sphere measurements is a central analytical challenge in pharmaceutical

Block-R1: Rethinking the Role of Block Size in Multi-domain Reinforcement Learning for Diffusion Large Language Models

arXiv:2605.11726v1 Announce Type: new Abstract: Recently, reinforcement learning (RL) has been widely applied during post-training for diffusion large language models (dLLMs) to enhance reasoning with

Blumira launches Kindling pilot, an agentic SIEM investigation engine that cuts alert volume up to 50x

model-releasessiliconangle

Security operations platform startup Blumira Inc. today launched the pilot of Kindling, an agentic security information and event management investigation engine that the company says can reduce alert

我們開源了這顆星球🌎上速度最快的低成本 bm25 引擎。

model-releasesemad-mostaque--x

我們開源了這顆星球🌎上速度最快的低成本 bm25 引擎。 so we built psql_bm25s. exact BM25 retrieval. native Postgres access method. ~23x faster than pg_search on the standard benchmark. retrieval stops being a budget item. the

Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation

arXiv:2605.12034v1 Announce Type: cross Abstract: Omni-modal language models are intended to jointly understand audio, visual inputs, and language, but benchmark gains can be inflated when visual evid

Breaking Down and Building Up: Mixture of Skill-Based Vision-and-Language Navigation Agents

arXiv:2508.07642v3 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) poses significant challenges for agents to interpret natural language instructions and navigate complex 3

Breaking extit{Winner-Takes-All}: Cooperative Policy Optimization Improves Diverse LLM Reasoning

arXiv:2605.11461v1 Announce Type: cross Abstract: Reinforcement learning with verifiers (RLVR) has become a central paradigm for improving LLM reasoning, yet popular group-based optimization algorithm

Built a local coding harness powered by Gemma 4. It runs locally, connects to my model backend, starts coding sessions, streams responses, a…

Built a local coding harness powered by Gemma 4. It runs locally, connects to my model backend, starts coding sessions, streams responses, and uses tools through a CLI-style workflow. Still early, but

model-releasesollama--x

CAD-feature enhanced machine learning for manufacturing effort estimation on sheet metal bending parts

arXiv:2605.12266v1 Announce Type: new Abstract: Graph-based machine learning has emerged as a promising approach for manufacturability analysis by learning directly from CAD models represented as Boun

Calibrated Multimodal Representation Learning with Missing Modalities

arXiv:2511.12034v2 Announce Type: replace Abstract: Multimodal representation learning harmonizes distinct modalities by aligning them into a unified latent space. Recent research generalizes traditio

Caraman at SemEval-2026 Task 8: Three-Stage Multi-Turn Retrieval with Query Rewriting, Hybrid Search, and Cross-Encoder Reranking

arXiv:2605.12028v1 Announce Type: new Abstract: We describe our system for SemEval-2026 Task 8 (MTRAGEval), participating in Task A (Retrieval) across four English-language domains. Our approach emplo

CATS: Cascaded Adaptive Tree Speculation for Memory-Limited LLM Inference Acceleration

arXiv:2605.11186v1 Announce Type: new Abstract: Auto-regressive decoding in Large Language Models (LLMs) is inherently memory-bound: every generation step requires loading the model weights and interm

Checkup2Action: A Multimodal Clinical Check-up Report Dataset for Patient-Oriented Action Card Generation

arXiv:2605.11533v1 Announce Type: new Abstract: Clinical check-up reports are multimodal documents that combine page layouts, tables, numerical biomarkers, abnormality flags, imaging findings, and dom

Chronicles-OCR: A Cross-Temporal Perception Benchmark for the Evolutionary Trajectory of Chinese Characters

arXiv:2605.11960v1 Announce Type: new Abstract: Vision Large Language Models (VLLMs) have achieved remarkable success in modern text-rich visual understanding. However, their perceptual robustness in

clarifying how much “task horizon” falls off as a function of the increasing accuracy criterion directly in the graph (not across tabs) woul…

model-releasesgary-marcus--x

clarifying how much “task horizon” falls off as a function of the increasing accuracy criterion directly in the graph (not across tabs) would definitely improve this graph, @METR_Evals. as a variant o

Claude Code and @suno have more in common than you might think: 'It's fun to build things, and it's fun to use what you build.' AI lets peop…

model-releasessonya-huang--x

Claude Code and @suno have more in common than you might think: 'It's fun to build things, and it's fun to use what you build.' AI lets people be creative in almost any domain, from coding to making m

Claude Code weekly limits are increasing 50%, now through July 13. Live now for all Pro, Max, Team, and seat-based Enterprise users.

model-releasesboris-cherny--x

Claude Code weekly usage limits have increased by 50% for all Pro, Max, Team, and seat-based Enterprise users, effective immediately through July 13. This temporary expansion applies across all user t

ClinicalBench: Stress-Testing Assertion-Aware Retrieval for Cross-Admission Clinical QA on MIMIC-IV

arXiv:2605.11143v1 Announce Type: new Abstract: Reasoning benchmarks measure clinical performance on clean inputs. We evaluate the step before reasoning: retrieval over real EHR notes, where negation,

Control of Fully Actuated Aerial Vehicles: A Comparison of Model-based and Sensor-based Dynamic Inversion

model-releasesarxiv-cs-ro

arXiv:2605.12071v1 Announce Type: new Abstract: Fully actuated multirotor platforms decouple translational force generation from vehicle attitude, enabling independent control of position and orientat

CORE: Cyclic Orthotope Relation Embedding for Knowledge Graph Completion

arXiv:2605.11159v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to automatically infer missing facts in multi-relational data by mapping entities and relations into continuous re

Correcting Selection Bias in Sparse User Feedback for Large Language Model Quality Estimation: A Multi-Agent Hierarchical Bayesian Approach

arXiv:2605.12177v1 Announce Type: new Abstract: [Abridged] Production LLM deployments receive feedback from a non-random fraction of users: thumbs sit mostly in the tails of the satisfaction distribut

Courtroom-Style Multi-Agent Debate with Progressive RAG and Role-Switching for Controversial Claim Verification

arXiv:2603.28488v2 Announce Type: replace Abstract: Large language models (LLMs) remain unreliable for high-stakes claim verification due to hallucinations and shallow reasoning. While retrieval-augme

Covering Human Action Space for Computer Use: Data Synthesis and Benchmark

arXiv:2605.12501v1 Announce Type: new Abstract: Computer-use agents (CUAs) automate on-screen work, as illustrated by GPT-5.4 and Claude. Yet their reliability on complex, low-frequency interactions i

Crash Assessment via Mesh-Based Graph Neural Networks and Physics-Aware Attention

arXiv:2605.11784v1 Announce Type: cross Abstract: Full-vehicle crash simulations are computationally expensive, limiting their use in iterative design exploration. This work investigates learned hybri

CSP Allow-list Experiment

model-releasessimon-willison

Tool: CSP Allow-list Experiment An experiment that shows that you can load an app in a CSP-protected sandboxed iframe (see previous note) and have a custom fetch() that intercepts CSP errors and passe

CTFusion: A CTF-based Benchmark for LLM Agent Evaluation

arXiv:2605.11504v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have enabled agentic systems for complex, multi-step tasks; cybersecurity is emerging as a prominent app

DarkQA: Benchmarking Vision-Language Models on Visual-Primitive Question Answering in Low-Light Indoor Scenes

arXiv:2512.24985v4 Announce Type: replace Abstract: Vision Language Models (VLMs) are increasingly adopted as central reasoning modules for embodied agents. Existing benchmarks evaluate their capabili

Decomposing Evolutionary Mixture-of-LoRA Architectures: The Routing Lever, the Lifecycle Penalty, and a Substrate-Conditional Boundary

arXiv:2605.11153v1 Announce Type: new Abstract: We decompose an evolutionary mixture-of-LoRA system on a from-scratch ~150M-parameter widened-D substrate (D=1536, V=32000; D/V approx 0.048; the 'widen

Delightful Gradients Accelerate Corner Escape

arXiv:2605.11908v1 Announce Type: new Abstract: Softmax policy gradient converges at O(1/t), but its transient behavior near sub-optimal corners of the simplex can be exponentially slow. The bottlenec

Deploying Self-Supervised Learning for Real Seismic Data Denoising

arXiv:2605.11109v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has emerged as a promising approach to seismic data denoising as it does not require clean reference data. In this work

Detecting Data Contamination in LLMs via In-Context Learning

arXiv:2510.27055v2 Announce Type: replace Abstract: We present Contamination Detection via Context (CoDeC), a practical and accurate method to detect and quantify training data contamination in large

DiFaReli++: Diffusion Face Relighting with Consistent Cast Shadows

arXiv:2304.09479v5 Announce Type: replace Abstract: We introduce a novel approach to single-view face relighting in the wild, addressing challenges such as global illumination and cast shadows. A comm

DiffScore: Text Evaluation Beyond Autoregressive Likelihood

arXiv:2605.11601v1 Announce Type: new Abstract: Autoregressive language models are widely used for text evaluation, however, their left-to-right factorization introduces positional bias, i.e., early t

DisagMoE: Computation-Communication overlapped MoE Training via Disaggregated AF-Pipe Parallelism

arXiv:2605.11005v1 Announce Type: new Abstract: Mixture-of-experts (MoE) architectures enable trillion-parameter LLMs with sparsely activated experts. Expert parallelism (EP) is a widely adopted MoE t

Distributed Pose Graph Optimization via Continuous Riemannian Dynamics

model-releasesarxiv-cs-ro

arXiv:2605.11210v1 Announce Type: new Abstract: We present a framework for distributed Pose Graph Optimization (PGO) by formulating the problem as a second-order continuous-time dynamical system evolv

Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics

arXiv:2605.12178v1 Announce Type: cross Abstract: World models enable agents to anticipate the effects of their actions by internalizing environment dynamics. In enterprise systems, however, these dyn

Drop the Act: Probe-Filtered RL for Faithful Chain-of-Thought Reasoning

arXiv:2605.11467v1 Announce Type: new Abstract: Reasoning models post-hoc rationalize answers they have already committed to internally, producing chains of *reasoning theater*: deliberative-looking s

Efficient Algorithms for Logistic Contextual Slate Bandits with Bandit Feedback

arXiv:2506.13163v3 Announce Type: replace Abstract: We study the Logistic Contextual Slate Bandit problem, where, at each round, an agent selects a slate of N items from an exponentially large set (of

Efficient and Adaptive Human Activity Recognition via LLM Backbones

arXiv:2605.12019v1 Announce Type: new Abstract: Human Activity Recognition (HAR) is a core task in pervasive computing systems, where models must operate under strict computational constraints while r

Efficient LLM Reasoning via Variational Posterior Guidance with Efficiency Awareness

arXiv:2605.11019v1 Announce Type: new Abstract: Although large language models rely on chain-of-thought for complex reasoning, the overthinking phenomenon severely degrades inference efficiency. Exist

EgoEV-HandPose: Egocentric 3D Hand Pose Estimation and Gesture Recognition with Stereo Event Cameras

arXiv:2605.12297v1 Announce Type: new Abstract: Egocentric 3D hand pose estimation and gesture recognition are essential for immersive augmented/virtual reality, human-computer interaction, and roboti

EsoLang-Bench: Evaluating Genuine Reasoning in Large Language Models via Esoteric Programming Languages

arXiv:2603.09678v2 Announce Type: replace-cross Abstract: Large language models achieve near-ceiling performance on code generation benchmarks, yet most of the programming languages used by popular be