model releases

Verifiable Environments Are LEGO Bricks: Recursive Composition for Reasoning Generalization

arXiv:2606.12373v1 Announce Type: new Abstract: Reinforcement Learning (RL) with verifiable environments has emerged as a powerful approach for enhancing the reasoning capabilities of Large Language M

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VICX: Generalizable Robot Manipulation via Video Generation and In-Context Operator Network

DGX agent

arXiv:2606.12028v1 Announce Type: new Abstract: Generalizable robot manipulation requires not only task-level reasoning over unseen scenes, but also reliable grounding of visual plans into embodiment-

model-releasesarxiv-cs-ro

11 Jun 2026

VietMed-MCQ: A Consistency-Filtered Data Synthesis Framework for Vietnamese Traditional Medicine Evaluation

arXiv:2601.03792v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable proficiency in general medical domains. However, their performance significantly degrades

Visualizing LLM Latent Space Geometry Through Dimensionality Reduction

model-releasesarxiv-cs-lg

arXiv:2511.21594v3 Announce Type: replace Abstract: Large language models (LLMs) achieve state-of-the-art results across many natural language tasks, but their internal mechanisms remain difficult to

VL-DINO: Leveraging CLIP Vision-Language Knowledge for Open-Vocabulary Object Detectio

arXiv:2606.11546v1 Announce Type: new Abstract: Vision-language models like CLIP can provide rich semantic priors for open-vocabulary object detection. However, jointly integrating both textual and vi

When Does Language Matter? Multilingual Instructions Reveal Step-wise Language Sensitivity in Vision-Language-Action Models

arXiv:2606.11906v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong performance in language-conditioned robotic manipulation, yet their robustness to linguistic varia

When Generic Prompt Improvements Hurt: Evaluation-Driven Iteration for LLM Applications

arXiv:2601.22025v2 Announce Type: replace-cross Abstract: Evaluating Large Language Model (LLM) applications differs from conventional software testing because outputs are probabilistic, semantically

When Roleplaying, Do Models Believe What They Say?

arXiv:2606.11502v1 Announce Type: cross Abstract: Language models can state that 'the Earth orbits the Sun' and, when role-playing Aristotle, assert the opposite. Recent work argues that persona adopt

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs

arXiv:2606.12385v1 Announce Type: new Abstract: Modern LLM training pipelines increasingly rely on other models to generate data, filter corpora, judge outputs, and guide development decisions. These

Wordle 1,817 3/6 ⬛⬛🟨⬛⬛ 🟨🟨🟨🟩⬛ 🟩🟩🟩🟩🟩

model-releasesanthropic--x

This post documents a Wordle puzzle solution (puzzle #1,817) completed in 3 attempts out of 6 allowed guesses, showing the progression of letter feedback (gray for incorrect letters, yellow for correc

World Model Self-Distillation: Training World Models to Solve General Tasks

arXiv:2606.12072v1 Announce Type: new Abstract: Pretrained video generators are promising visual world models that exhibit emergent task-solving abilities; however, their reliance on detailed textual

World Pilot: Steering Vision-Language-Action Models with World-Action Priors

model-releasesarxiv-cs-ro

arXiv:2606.12403v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit semantic grounding from large-scale pretraining and perform competently across in-distribution manipulation

WorldReasoner: Evaluating Whether Language Model Agents Forecast Events with Valid Reasoning

arXiv:2606.11816v1 Announce Type: cross Abstract: Forecasting real-world events requires language-model agents to reason under uncertainty from incomplete, time-bounded information. Yet evaluating whe

5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning

arXiv:2606.10488v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT) methods provide a streamlined and efficient tool for adapting large models to domain-specific multimodal downstre

A complementary study on PlanGPT: Evaluation with defined Performance Metrics and comparison with a planner

arXiv:2606.10489v1 Announce Type: new Abstract: Automated Planning is a subfield of Artificial Intelligence (AI) where the main objective is generating a sequence of actions, known as a plan, that hel

A Constrained Natural-Language Interface for Variational Multi-Physics Finite Element Simulations in FEniCS

arXiv:2606.10928v1 Announce Type: cross Abstract: Large language models can reduce the manual effort required to set up finite element simulations, but they introduce reliability risks when generated

A History-Aware Visually Grounded Critic for Computer Use Agents

arXiv:2606.11078v1 Announce Type: new Abstract: Various test-time interventions for Computer Use Agents (CUAs), including critic models, have been developed to improve performance through pre-executio

A Large Scale Open-Source Image and Video Dataset for Robust Wildfire Detection and Classification

arXiv:2606.10174v1 Announce Type: new Abstract: Wildfire detection and monitoring are critical for mitigating fire spread and reducing environmental and infrastructural damage. In this work, we introd

A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI

arXiv:2505.01458v2 Announce Type: replace-cross Abstract: Navigation and manipulation are core capabilities in Embodied AI, but training agents to perform them directly in the real world is costly, ti

ABC-Bench: An Agentic Bio-Capabilities Benchmark for Biosecurity

arXiv:2606.11150v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly acquiring capabilities relevant to biological research, from literature synthesis to interpretation of experime

Achieving Cloud-Grade SLOs for Local Mixture-of-Experts Inference through CPU-GPU Hybrid Design

arXiv:2606.10493v1 Announce Type: cross Abstract: Local deployment of large Mixture-of-Experts (MoE) models falls short of the service quality achieved in cloud-scale environments, even under low-conc

AdaGC: Enhancing LLM Pretraining Stability via Adaptive Gradient Clipping

model-releasesarxiv-cs-lg

arXiv:2502.11034v3 Announce Type: replace Abstract: Loss spikes remain a persistent obstacle in large-scale language model pretraining. While previous research has attempted to identify the root cause

Advancing the State-of-the-Art in Empirical Privacy Auditing

arXiv:2606.10481v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning of large language models (LLMs) can exhibit problematic memorization of individual training examples. Empirical privac

Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis

arXiv:2606.10381v1 Announce Type: cross Abstract: Muon collider research spans accelerator physics, detector instrumentation, and high-energy phenomenology, with relevant evidence scattered across a r

AgenticNav: Zero-Shot Vision-and-Language Navigation as a Tool-Calling Harness

model-releasesarxiv-cs-ro

arXiv:2606.10577v1 Announce Type: new Abstract: Zero-shot vision-and-language navigation in continuous environments (VLN-CE) has recently become feasible with large vision-language models (VLMs). Howe

AgniNav: Configuration-Driven Cross-Embodiment Local Planning for Robot Navigation

model-releasesarxiv-cs-ro

arXiv:2606.10903v1 Announce Type: new Abstract: Monocular local navigation is attractive for lightweight robots, but existing vision-based policies often couple perception to a specific body, camera h

[AINews] Anthropic Claude Fable 5 — Mythos but Safe, with Controversial Terms

model-releaseslatent-space

This article from Latent Space discusses Anthropic's Claude Fable 5 model, examining its capabilities in handling creative and mythological content while maintaining safety guardrails, along with cove

Alignment Collapse Under KV Cache Quantization: Diagnosis and Mitigation

arXiv:2606.09864v1 Announce Type: cross Abstract: Key-value (KV) cache quantization is widely used to reduce Large Language Model (LLM) inference memory, yet existing evaluations solely focus on measu

An adaptive framework for the axisymmetric pulsar magnetosphere using physics-informed Kolmogorov-Arnold networks

model-releasesarxiv-cs-lg

arXiv:2606.10686v1 Announce Type: cross Abstract: The pulsar magnetosphere has only recently been addressed using Physics-Informed Neural Networks (PINNs), by deploying a domain-decomposition approach

An Industrial-Scale Insurance LLM Achieving Verifiable Domain Mastery and Hallucination Control without Competence Trade-offs

arXiv:2603.14463v2 Announce Type: replace Abstract: Adapting Large Language Models (LLMs) to high-stakes vertical domains like insurance presents a significant challenge: scenarios demand strict adher

and the video for reference: https://x.com/ClaudeDevs/status/2064399512664526853 (I didnt get to use the updated designs in time)

and the video for reference: https://x.com/ClaudeDevs/status/2064399512664526853 (I didnt get to use the updated designs in time) Claude Fable 5 changed how we work on the Claude Code team day to day.

model-releasesthariq--x

Announcing the Gemma challenge! Google, Hugging Face, and the open-source AI community choose to empower AI builders rather than sabotage th…

model-releasesclem-delangue--x

Announcing the Gemma challenge! Google, Hugging Face, and the open-source AI community choose to empower AI builders rather than sabotage them. Fun to see the Hub becoming the platform where agents co

Anomaly Detection and Root Cause Analysis for Microservice Systems

arXiv:2606.09942v1 Announce Type: cross Abstract: Microservice systems are widely used to build cloud applications, yet their complexity makes failures inevitable, degrading user experience and causin

Anthropic backtracks on a policy limiting Claude Fable 5's ability to develop other AI models, after significant backlash from the AI research community (Maxwell Zeff/Wired)

Maxwell Zeff / Wired: Anthropic backtracks on a policy limiting Claude Fable 5's ability to develop other AI models, after significant backlash from the AI research community — The company changed cou

model-releasestechmeme

Anthropic secretly limiting Claude's usefulness for LLM development strengthens the argument that Anthropic is using AI safety to justify monopolistic behavior (Dean W. Ball/@deanwball)

Dean W. Ball / @deanwball: Anthropic secretly limiting Claude's usefulness for LLM development strengthens the argument that Anthropic is using AI safety to justify monopolistic behavior — My last obs

model-releasestechmeme

As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development 'Any topic related to buil…

model-releasesyann-lecun--x

As believers of open research, we are disappointed to see Anthropic silently degrading Fable 5 for AI development 'Any topic related to building pretraining pipelines, distributed training infrastruct

ASA: Backbone-Training-Free Representation Engineering for Tool-Calling Agents

arXiv:2602.04935v3 Announce Type: replace-cross Abstract: Adapting LLM agents to domain-specific tool calling remains notably brittle under evolving interfaces. Prompt and schema engineering is easy t

Assessing Automated Prompt Injection Attacks in Agentic Environments

arXiv:2606.10525v1 Announce Type: cross Abstract: Indirect prompt injection poses a critical threat to LLM agents that interact with untrusted external data, yet automated attack methods--proven effec

ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark

arXiv:2505.23851v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly applied to symbolic mathematics, yet existing evaluations often conflate pattern memorization wi

at Code w/ Claude Tokyo! say hi if you see me around

Thariq posted about attending a coding event or workshop featuring Claude in Tokyo and invited others to say hello if they encountered him there. The post appears to be a social announcement about his

model-releasesthariq--x

Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It

arXiv:2606.11052v1 Announce Type: new Abstract: Chain-of-thought (CoT) supervised fine-tuning (SFT) is widely adopted to improve reasoning ability, yet we find that it systematically degrades long-con

Attention Expansion: Enhancing Keyphrase Extraction from Long Documents with Attention-Augmented Contextualized Embeddings

arXiv:2606.10716v1 Announce Type: cross Abstract: Pre-trained language models (PLMs) have achieved strong performance in keyphrase extraction (KPE), largely due to their ability to generate rich conte

au-Rec: A Verifiable Benchmark for Agentic Recommender Systems

arXiv:2606.10156v1 Announce Type: cross Abstract: As recommender systems transition toward agentic, multi-turn conversational interfaces, evaluation paradigms have struggled to keep pace. Current benc

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

arXiv:2407.20242v5 Announce Type: replace-cross Abstract: Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language und

Benchmarking and Exploring the Capabilities of LLMs for Attack Investigations

arXiv:2606.10281v1 Announce Type: cross Abstract: This paper presents AuditBench, a new benchmark dataset for evaluating the capabilities of LLMs at investigating security-related system audit logs. W

Benchmarking Knowledge Editing using Logical Rules

arXiv:2606.10554v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications that require access to up-to-date knowledge. However, retraining LLM

Benchmarking stereo reconstruction for 3D printable Martian terrain models

arXiv:2606.10364v1 Announce Type: new Abstract: Reconstructing printable 3D models from Mars rover imagery is challenging because Martian terrain is low-texture, irregular, and partially observed. We

BenSyc: Benchmarking Conversational Sycophancy and Human Alignment in LLMs for Bengali Contexts

arXiv:2606.10061v1 Announce Type: new Abstract: Large language models (LLMs) increasingly participate in emotionally sensitive social conversations, where responses may shift from balanced support tow