Search: “model-releases”

VP-VLA: Visual Prompting as an Interface for Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2603.22003v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models typically map visual observations and linguistic instructions directly to robotic control signals. This 'black-b

Model Releases

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments

DGX agent

arXiv:2506.02387v3 Announce Type: replace Abstract: Recent advancements in Vision Language Models (VLMs) have expanded their capabilities to interactive agent tasks, yet existing benchmarks remain lim

model-releasesarxiv-cs-ai

14 Apr 2026

WaveMoE: A Wavelet-Enhanced Mixture-of-Experts Foundation Model for Time Series Forecasting

arXiv:2604.10544v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have recently achieved remarkable success in universal forecasting by leveraging large-scale pretraining on dive

WBCBench 2026: A Challenge for Robust White Blood Cell Classification Under Class Imbalance

arXiv:2604.10797v1 Announce Type: new Abstract: We present WBCBench 2026, an ISBI challenge and benchmark for automated WBC classification designed to stress-test algorithms under three key difficulti

WearBCI Dataset: Understanding and Benchmarking Real-World Wearable Brain-Computer Interfaces Signals

arXiv:2604.09649v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) have opened new platforms for human-computer interaction, medical diagnostics, and neurorehabilitation. Wearable BCI

WebForge: Breaking the Realism-Reproducibility-Scalability Trilemma in Browser Agent Benchmark

arXiv:2604.10988v1 Announce Type: new Abstract: Existing browser agent benchmarks face a fundamental trilemma: real-website benchmarks lack reproducibility due to content drift, controlled environment

We’re expanding Trusted Access for Cyber with additional tiers for authenticated cybersecurity defenders. Customers in the highest tiers can…

We’re expanding Trusted Access for Cyber with additional tiers for authenticated cybersecurity defenders. Customers in the highest tiers can request access to GPT-5.4-Cyber, a version of GPT-5.4 fine-

model-releasesopenai--x

We've been working on this for a while. Can't wait to hear what you think

model-releasesboris-cherny--x

We've been working on this for a while. Can't wait to hear what you think We've redesigned Claude Code on desktop. You can now run multiple Claude sessions side by side from one window, with a new sid

We've tested new OSS models the moment they're released for a while at Lindy. Inference is our #1 cost by a lot (more than payroll) — cuttin…

model-releasesharrison-chase--x

We've tested new OSS models the moment they're released for a while at Lindy. Inference is our #1 cost by a lot (more than payroll) — cutting it by 2-5x would be transformative. Last year, OSS models

What and Where to Adapt: Structure-Semantics Co-Tuning for Machine Vision Compression via Synergistic Adapters

arXiv:2604.10017v1 Announce Type: new Abstract: Parameter-efficient fine-tuning of pre-trained codecs is a promising direction in image compression for human and machine vision. While most existing wo

What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction

arXiv:2407.08101v4 Announce Type: replace Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, wher

What Users Leave Unsaid: Under-Specified Queries Limit Vision-Language Models

arXiv:2601.06165v2 Announce Type: replace-cross Abstract: Current vision-language benchmarks predominantly feature well-structured questions with clear, explicit prompts. However, real user queries ar

When Meaning Isn't Literal: Exploring Idiomatic Meaning Across Languages and Modalities

arXiv:2604.10787v1 Announce Type: new Abstract: Idiomatic reasoning, deeply intertwined with metaphor and culture, remains a blind spot for contemporary language models, whose progress skews toward su

Who Gets Which Message? Auditing Demographic Bias in LLM-Generated Targeted Text

arXiv:2601.17172v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly capable of generating personalized, persuasive text at scale, raising new questions about bias a

Who Wrote This Line? Evaluating the Detection of LLM-Generated Classical Chinese Poetry

arXiv:2604.10101v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has extended text generation tasks into the literary domain. However, AI-generated literary creati

Why does the upgrade button looks like Gemini logo 🤨

This Reddit post from r/ChatGPT is a user-generated discussion in which a member notices that ChatGPT's upgrade button visually resembles Google's Gemini logo — a star-like, multi-pointed sparkle icon

model-releasesr-chatgpt

Why I just quit Claude Pro after 48 hours (Rate Limit Anxiety)

A Reddit post on r/ChatGPT in which a user describes canceling their Claude Pro subscription within 48 hours, citing frustration with Claude's usage rate limits as the primary reason. The post reflect

model-releasesr-chatgpt

Why Smaller Is Slower? Dimensional Misalignment in Compressed LLMs

arXiv:2604.09595v1 Announce Type: cross Abstract: Post-training compression reduces LLM parameter counts but often produces irregular tensor dimensions that degrade GPU performance -- a phenomenon we

Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics

arXiv:2602.02343v3 Announce Type: replace-cross Abstract: Methods for controlling large language models (LLMs), including local weight fine-tuning, LoRA-based adaptation, and activation-based interven

Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models

arXiv:2604.10079v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) is the standard approach for adapting large language models (LLMs) to downstream tasks. However, we observe a persistent fa

Woosh: A Sound Effects Foundation Model

arXiv:2604.01929v2 Announce Type: replace-cross Abstract: The audio research community depends on open generative models as foundational tools for building novel approaches and establishing baselines.

Wordle 1,759 3/6 ⬛⬛⬛⬛🟨 🟨🟨🟨⬛⬛ 🟩🟩🟩🟩🟩

model-releasesanthropic--x

Anthropic's official X (Twitter) account shared a Wordle result showing the puzzle was solved in 3 out of 6 attempts for Wordle #1,759. The grid reveals the solver had no correct letters in the first

You Only Judge Once: Multi-response Reward Modeling in a Single Forward Pass

arXiv:2604.10966v1 Announce Type: cross Abstract: We present a discriminative multimodal reward model that scores all candidate responses in a single forward pass. Conventional discriminative reward m

Your Model Diversity, Not Method, Determines Reasoning Strategy

arXiv:2604.10827v1 Announce Type: new Abstract: Compute scaling for LLM reasoning requires allocating budget between exploring solution approaches (breadth) and refining promising solutions (depth). M

YUV20K: A Complexity-Driven Benchmark and Trajectory-Aware Alignment Model for Video Camouflaged Object Detection

arXiv:2604.09985v1 Announce Type: new Abstract: Video Camouflaged Object Detection (VCOD) is currently constrained by the scarcity of challenging benchmarks and the limited robustness of models agains

ZARA: Training-Free Motion Time-Series Reasoning via Evidence-Grounded LLM Agents

arXiv:2508.04038v2 Announce Type: replace Abstract: Motion sensor time-series are central to Human Activity Recognition (HAR), yet conventional approaches are constrained to fixed activity sets and ty

4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation

arXiv:2512.17012v3 Announce Type: replace Abstract: Despite advances in Multimodal LLMs (MLLMs), their ability to reason over 3D structures and temporal dynamics remains limited, constrained by weak 4

A Benchmark of Dexterity for Anthropomorphic Robotic Hands

model-releasesarxiv-cs-ro

arXiv:2604.09294v1 Announce Type: new Abstract: Dexterity is a central yet ambiguously defined concept in the design and evaluation of anthropomorphic robotic hands. In practice, the term is often use

A Compact Hybrid Convolution--Frequency State Space Network for Learned Image Compression

arXiv:2511.20151v2 Announce Type: replace Abstract: Learned image compression (LIC) has recently benefited from Transformer- and state space models (SSM)- based backbones for modeling long-range depen

A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need

arXiv:2604.08749v1 Announce Type: new Abstract: How many of a neural network's parameters actually encode task-specific information? We investigate this question with LottaLoRA, a training paradigm in

Accelerating Local LLMs on Resource-Constrained Edge Devices via Distributed Prompt Caching

arXiv:2602.22812v2 Announce Type: replace Abstract: Since local LLM inference on resource-constrained edge devices imposes a severe performance bottleneck, this paper proposes distributed prompt cachi

Accurate and Reliable Uncertainty Estimates for Deterministic Predictions Extensions to Under and Overpredictions

arXiv:2604.08755v1 Announce Type: cross Abstract: Computational models support high-stakes decisions across engineering and science, and practitioners increasingly seek probabilistic predictions to qu

Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Search

arXiv:2509.26435v2 Announce Type: replace-cross Abstract: Controllable summarization moves beyond generic outputs toward human-aligned summaries guided by specified attributes. In practice, the interd

Adaptive Rigor in AI System Evaluation using Temperature-Controlled Verdict Aggregation via Generalized Power Mean

arXiv:2604.08595v1 Announce Type: cross Abstract: Existing evaluation methods for LLM-based AI systems, such as LLM-as-a-Judge, verdict systems, and NLI, do not always align well with human assessment

Adaptive Simulation Experiment for LLM Policy Optimization

arXiv:2604.08779v1 Announce Type: new Abstract: Large language models (LLMs) have significant potential to improve operational efficiency in operations management. Deploying these models requires spec

Adaptive Tuning of Parameterized Traffic Controllers via Multi-Agent Reinforcement Learning

arXiv:2512.07417v2 Announce Type: replace Abstract: Effective traffic control is essential for mitigating congestion in transportation networks. Conventional traffic management strategies, including r

AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments

arXiv:2604.06111v2 Announce Type: replace Abstract: Existing Agent benchmarks suffer from two critical limitations: high environment interaction overhead (up to 41% of total evaluation time) and imbal

Agentic Jackal: Live Execution and Semantic Value Grounding for Text-to-JQL

arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com

Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems

arXiv:2604.08963v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) are increasingly deployed for complex workflows, their emergent properties-particularly the accumulation of bias-remai

ALMAB-DC: Active Learning, Multi-Armed Bandits, and Distributed Computing for Sequential Experimental Design and Black-Box Optimization

arXiv:2603.21180v3 Announce Type: replace Abstract: Sequential experimental design under expensive, gradient-free objectives is a central challenge in computational statistics: evaluation budgets are

AlphaLab: Autonomous Multi-Agent Research Across Optimization Domains with Frontier LLMs

arXiv:2604.08590v1 Announce Type: cross Abstract: We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full experimental cycle in quanti

ALTO: Adaptive LoRA Tuning and Orchestration for Heterogeneous LoRA Training Workloads

arXiv:2604.05426v2 Announce Type: replace-cross Abstract: Low-Rank Adaptation (LoRA) is now the dominant method for parameter-efficient fine-tuning of large language models, but achieving a high-quali

Anchored Sliding Window: Toward Robust and Imperceptible Linguistic Steganography

arXiv:2604.09066v1 Announce Type: new Abstract: Linguistic steganography based on language models typically assumes that steganographic texts are transmitted without alteration, making them fragile to

Armageddon awaits the Senate GOP if we don’t get the SAVE America Act passed into law Let’s freaking go!

model-releaseselon-musk--x

Armageddon awaits the Senate GOP if we don’t get the SAVE America Act passed into law Let’s freaking go! McLaughlin poll released today shows 1 in 8 would-be GOP voters stay home in the midterms in ME

AssemLM: Spatial Reasoning Multimodal Large Language Models for Robotic Assembly

model-releasesarxiv-cs-ro

arXiv:2604.08983v1 Announce Type: new Abstract: Spatial reasoning is a fundamental capability for embodied intelligence, especially for fine-grained manipulation tasks such as robotic assembly. While

AsymLoc: Towards Asymmetric Feature Matching for Efficient Visual Localization

arXiv:2604.09445v1 Announce Type: new Abstract: Precise and real-time visual localization is critical for applications like AR/VR and robotics, especially on resource-constrained edge devices such as

AudioGuard: Toward Comprehensive Audio Safety Protection Across Diverse Threat Models

arXiv:2604.08867v1 Announce Type: cross Abstract: Audio has rapidly become a primary interface for foundation models, powering real-time voice assistants. Ensuring safety in audio systems is inherentl

Automated Batch Distillation Process Simulation for a Large Hybrid Dataset for Deep Anomaly Detection

arXiv:2604.09166v1 Announce Type: new Abstract: Anomaly detection (AD) in chemical processes based on deep learning offers significant opportunities but requires large, diverse, and well-annotated tra