Search: “model-releases”

Think in Sentences: Explicit Sentence Boundaries Enhance Language Model's Capabilities

arXiv:2604.10135v1 Announce Type: cross Abstract: Researchers have explored different ways to improve large language models (LLMs)' capabilities via dummy token insertion in contexts. However, existin

Model Releases

Think Parallax: Solving Multi-Hop Problems via Multi-View Knowledge-Graph-Based Retrieval-Augmented Generation

DGX agent

arXiv:2510.15552v3 Announce Type: replace-cross Abstract: Large language models (LLMs) still struggle with multi-hop reasoning over knowledge-graphs (KGs), and we identify a previously overlooked stru

model-releasesarxiv-cs-ai

14 Apr 2026

Thinking Fast, Thinking Wrong: Intuitiveness Modulates LLM Counterfactual Reasoning in Policy Evaluation

arXiv:2604.10511v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for causal and counterfactual reasoning, yet their reliability in real-world policy evaluation remain

This is why we released liteparse :) Free, open-source, designed for agents. Natively supports OCR / screenshotting for deeper visual unders…

model-releasesjerry-liu--x

This is why we released liteparse :) Free, open-source, designed for agents. Natively supports OCR / screenshotting for deeper visual understanding in a document when needed. @kepano I just tried it t

Three Roles, One Model: Role Orchestration at Inference Time to Close the Performance Gap Between Small and Large Agents

arXiv:2604.11465v1 Announce Type: new Abstract: Large language model (LLM) agents show promise on realistic tool-use tasks, but deploying capable agents on modest hardware remains challenging. We stud

Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory

arXiv:2604.11544v1 Announce Type: cross Abstract: Structured memory representations such as knowledge graphs are central to autonomous agents and other long-lived systems. However, most existing appro

TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale

arXiv:2604.10291v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown promising performance in time series modeling tasks, but do they truly understand time series data? While multip

TinyGaze: Lightweight Gaze-Gesture Recognition on Commodity Mobile Devices

arXiv:2604.09658v1 Announce Type: cross Abstract: Gaze gestures can provide hands free input on mobile devices, but practical use requires (i) gestures users can learn and recall and (ii) recognition

Today we're launching a rebuilt version of Claude Code on desktop. The app has been redesigned for the ground up to make it easier than ever…

Today we're launching a rebuilt version of Claude Code on desktop. The app has been redesigned for the ground up to make it easier than ever to parallelize work with Claude. I haven't opened an IDE or

model-releasesthariq--x

Token-Budget-Aware Pool Routing for Cost-Efficient LLM Inference

arXiv:2604.09613v1 Announce Type: cross Abstract: Production vLLM fleets provision every instance for worst-case context length, wasting 4-8x concurrency on the 80-95% of requests that are short and s

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models

arXiv:2604.10733v1 Announce Type: cross Abstract: Large language models increasingly serve as conversational agents that adopt personas and role-play characters at user request. This capability, while

Topo-ADV: Generating Topology-Driven Imperceptible Adversarial Point Clouds

arXiv:2604.09879v1 Announce Type: new Abstract: Deep neural networks for 3D point cloud understanding have achieved remarkable success in object classification and recognition, yet recent work shows t

TorchUMM: A Unified Multimodal Model Codebase for Evaluation, Analysis, and Post-training

arXiv:2604.10784v1 Announce Type: new Abstract: Recent advances in unified multimodal models (UMMs) have led to a proliferation of architectures capable of understanding, generating, and editing acros

Toward Generalized Cross-Lingual Hateful Language Detection with Web-Scale Data and Ensemble LLM Annotations

arXiv:2604.09625v1 Announce Type: new Abstract: We study whether large-scale unlabelled web data and LLM-based synthetic annotations can improve multilingual hate speech detection. Starting from texts

Towards Multi-Source Domain Generalization for Sleep Staging with Noisy Labels

arXiv:2604.10009v1 Announce Type: cross Abstract: Automatic sleep staging is a multimodal learning problem involving heterogeneous physiological signals such as EEG and EOG, which often suffer from do

Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs

arXiv:2604.10480v1 Announce Type: new Abstract: Post-training data plays a pivotal role in shaping the capabilities of Large Language Models (LLMs), yet datasets are often treated as isolated artifact

Tracking High-order Evolutions via Cascading Low-rank Fitting

arXiv:2604.10980v1 Announce Type: new Abstract: Diffusion models have become the de facto standard for modern visual generation, including well-established frameworks such as latent diffusion and flow

Training-Free Object-Background Compositional T2I via Dynamic Spatial Guidance and Multi-Path Pruning

arXiv:2604.09850v1 Announce Type: new Abstract: Existing text-to-image diffusion models, while excelling at subject synthesis, exhibit a persistent foreground bias that treats the background as a pass

TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection

arXiv:2604.10386v1 Announce Type: new Abstract: Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support earlier detection and improved care, but modeling su

TraversalBench: Challenging Paths to Follow for Vision Language Models

arXiv:2604.10999v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on many multimodal benchmarks. However, the ability to follow complex visual paths -- a task that human o

Trust Your Memory: Verifiable Control of Smart Homes through Reinforcement Learning with Multi-dimensional Rewards

arXiv:2604.10110v1 Announce Type: new Abstract: Large Language Models (LLMs) have become a key foundation for enabling personalized smart home experiences. While existing studies have explored how sma

Trusted access for the next era of cyber defense

OpenAI is expanding trusted access to its AI models for cybersecurity purposes, enabling vetted researchers, defenders, and organizations to leverage advanced AI capabilities for cyber defense applica

model-releasesopenai

TS-Haystack: A Multi-Scale Retrieval Benchmark for Time Series Language Models

arXiv:2602.14200v4 Announce Type: replace Abstract: Time Series Language Models (TSLMs) are emerging as unified models for reasoning over continuous signals in natural language. However, long-context

Tuning Qwen2.5-VL to Improve Its Web Interaction Skills

arXiv:2604.09571v1 Announce Type: cross Abstract: Recent advances in vision-language models (VLMs) have sparked growing interest in using them to automate web tasks, yet their feasibility as independe

Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization

arXiv:2604.09574v1 Announce Type: new Abstract: The rise of autonomous GUI agents has triggered adversarial countermeasures from digital platforms, yet existing research prioritizes utility and robust

Turn your best AI prompts into one-click tools in Chrome

Google has launched **Skills in Chrome**, a feature that lets users save and reuse their most helpful Gemini AI prompts and run them with a single click. When a useful prompt is written in Gemini, it

model-releasesgoogle-ai

Turning Generators into Retrievers: Unlocking MLLMs for Natural Language-Guided Geo-Localization

arXiv:2604.10721v1 Announce Type: cross Abstract: Natural-language Guided Cross-view Geo-localization (NGCG) aims to retrieve geo-tagged satellite imagery using textual descriptions of ground scenes.

Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any f…

model-releasesharrison-chase--x

Two major shifts will be seen in Agentic AI after Harness and YOU MUST KNOW. 1. Workflow design of your agents matters a lot more than any frontier model selection. Till now we have mostly focused on

Uber CTO Praveen Neppalli Naga says the company's surging use of AI coding tools has maxed out its full-year AI budget just a few months into 2026 (Laura Bratton/The Information)

Laura Bratton / The Information: Uber CTO Praveen Neppalli Naga says the company's surging use of AI coding tools has maxed out its full-year AI budget just a few months into 2026 — Uber's surging use

model-releasestechmeme

UK gov's Mythos AI tests help separate cybersecurity threat from hype

model-releasesars-technica

The UK's AI Security Institute (AISI) conducted evaluations of Anthropic's Claude Mythos Preview, finding it represents a meaningful step up over previous frontier AI models in cybersecurity capabilit

Ultra-Low-Dimensional Prompt Tuning via Random Projection

arXiv:2502.04501v3 Announce Type: replace Abstract: Large language models achieve state-of-the-art performance but are increasingly costly to fine-tune. Prompt tuning is a parameter-efficient fine-tun

Uncertainty-quantified Pulse Signal Recovery from Facial Video using Regularized Stochastic Interpolants

arXiv:2604.10777v1 Announce Type: new Abstract: Imaging Photoplethysmography (iPPG), an optical procedure which recovers a human's blood volume pulse (BVP) waveform using pixel readout from a camera,

Unified Graph Prompt Learning via Low-Rank Graph Message Prompting

arXiv:2604.11257v1 Announce Type: new Abstract: Graph Data Prompt (GDP), which introduces specific prompts in graph data for efficiently adapting pre-trained GNNs, has become a mainstream approach to

Unified Removal of Raindrops and Reflections: A New Benchmark and A Novel Pipeline

arXiv:2603.16446v3 Announce Type: replace Abstract: When capturing images through glass surfaces or windshields on rainy days, raindrops and reflections frequently co-occur to significantly reduce the

Unifying Ontology Construction and Semantic Alignment for Deterministic Enterprise Reasoning at Scale

arXiv:2604.09608v1 Announce Type: new Abstract: While enterprises amass vast quantities of data, much of it remains chaotic and effectively dormant, preventing decision-making based on comprehensive i

UniToolCall: Unifying Tool-Use Representation, Data, and Evaluation for LLM Agents

arXiv:2604.11557v1 Announce Type: new Abstract: Tool-use capability is a fundamental component of LLM agents, enabling them to interact with external systems through structured function calls. However

Unsupervised Detection of Spatiotemporal Anomalies in PMU Data Using Transformer-Based BiGAN

arXiv:2509.25612v2 Announce Type: replace-cross Abstract: Ensuring power grid resilience requires the timely and unsupervised detection of anomalies in synchrophasor data streams. We introduce T-BiGAN

Unsupervised Domain Adaptation for Binary Classification with an Unobservable Source Subpopulation

arXiv:2509.20587v3 Announce Type: replace-cross Abstract: We study an unsupervised domain adaptation problem where the source domain consists of subpopulations defined by the binary label Y and a bina

Users accuse Anthropic of degrading Claude Opus 4.6's and Claude Code's performance; the startup's employees publicly deny it degrades models to manage capacity (Carl Franzen/VentureBeat)

Carl Franzen / VentureBeat: Users accuse Anthropic of degrading Claude Opus 4.6's and Claude Code's performance; the startup's employees publicly deny it degrades models to manage capacity — A growing

model-releasestechmeme

Valence-Arousal Subspace in LLMs: Circular Emotion Geometry and Multi-Behavioral Control

arXiv:2604.03147v2 Announce Type: replace-cross Abstract: We present a method to identify a valence-arousal (VA) subspace within large language model representations. From 211k emotion-labeled texts,

Variable Selection Using Relative Importance Rankings

arXiv:2509.10853v2 Announce Type: replace-cross Abstract: Although conceptually related, variable selection and relative importance (RI) analysis have been treated quite differently in the literature.

VeriInteresting: An Empirical Study of Model Prompt Interactions in Verilog Code Generation

arXiv:2603.08715v2 Announce Type: replace-cross Abstract: Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between mod

VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation

arXiv:2604.10127v1 Announce Type: cross Abstract: The rapid advancement of AIGC-based video generation has underscored the critical need for comprehensive evaluation frameworks that go beyond traditio

VGGT-HPE: Reframing Head Pose Estimation as Relative Pose Prediction

arXiv:2604.10106v1 Announce Type: new Abstract: Monocular head pose estimation is traditionally formulated as direct regression from a single image to an absolute pose. This paradigm forces the networ

VidAudio-Bench: Benchmarking V2A and VT2A Generation across Four Audio Categories

arXiv:2604.10542v1 Announce Type: cross Abstract: Video-to-Audio (V2A) generation is essential for immersive multimedia experiences, yet its evaluation remains underexplored. Existing benchmarks typic

Virtual Smart Metering in District Heating Networks via Heterogeneous Spatial-Temporal Graph Neural Networks

arXiv:2604.10166v1 Announce Type: cross Abstract: Intelligent operation of thermal energy networks aims to improve energy efficiency, reliability, and operational flexibility through data-driven contr

Vision-Language-Action Model, Robustness, Multi-modal Learning, Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2604.10055v1 Announce Type: new Abstract: Despite their strong performance in embodied tasks, recent Vision-Language-Action (VLA) models remain highly fragile under multimodal perturbations, whe

VLN-NF: Feasibility-Aware Vision-and-Language Navigation with False-Premise Instructions

arXiv:2604.10533v1 Announce Type: cross Abstract: Conventional Vision-and-Language Navigation (VLN) benchmarks assume instructions are feasible and the referenced target exists, leaving agents ill-equ