Search: “model-releases”

SignReasoner: Compositional Reasoning for Complex Traffic Sign Understanding via Functional Structure Units

arXiv:2604.10436v1 Announce Type: new Abstract: Accurate semantic understanding of complex traffic signs-including those with intricate layouts, multi-lingual text, and composite symbols-is critical f

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Model Releases

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors

DGX agent

arXiv:2510.17516v4 Announce Type: replace-cross Abstract: Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only i

model-releasesarxiv-cs-ai

14 Apr 2026

Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation

model-releasesarxiv-cs-ro

arXiv:2604.10548v1 Announce Type: new Abstract: Obstacle avoidance is a fundamental vision-based task essential for enabling quadrotors to perform advanced applications. When planning the trajectory,

Simulating Organized Group Behavior: New Framework, Benchmark, and Analysis

arXiv:2604.09874v1 Announce Type: new Abstract: Simulating how organized groups (e.g., corporations) make decisions (e.g., responding to a competitor's move) is essential for understanding real-world

Simulator Adaptation for Sim-to-Real Learning of Legged Locomotion via Proprioceptive Distribution Matching

model-releasesarxiv-cs-ro

arXiv:2604.11090v1 Announce Type: new Abstract: Simulation trained legged locomotion policies often exhibit performance loss on hardware due to dynamics discrepancies between the simulator and the rea

Single-Agent LLMs Outperform Multi-Agent Systems on Multi-Hop Reasoning Under Equal Thinking Token Budgets

arXiv:2604.02460v2 Announce Type: replace Abstract: Recent work reports strong performance from multi-agent LLM systems (MAS), but these gains are often confounded by increased test-time computation.

SLM Finetuning for Natural Language to Domain Specific Code Generation in Production

arXiv:2604.09952v1 Announce Type: new Abstract: Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficul

SMART: When is it Actually Worth Expanding a Speculative Tree?

arXiv:2604.09731v1 Announce Type: cross Abstract: Tree-based speculative decoding accelerates autoregressive generation by verifying a branching tree of draft tokens in a single target-model forward p

SMFormer: Empowering Self-supervised Stereo Matching via Foundation Models and Data Augmentation

arXiv:2604.10218v1 Announce Type: new Abstract: Recent self-supervised stereo matching methods have made significant progress. They typically rely on the photometric consistency assumption, which pres

SmileyLlama: Modifying Large Language Models for Directed Chemical Space Exploration

arXiv:2409.02231v5 Announce Type: replace-cross Abstract: We show that large language model (LLMs) can be transformed via supervised fine-tuning (SFT) of engineered prompts into SmileyLlama for explor

SODA: Semi On-Policy Black-Box Distillation for Large Language Models

arXiv:2604.03873v2 Announce Type: replace-cross Abstract: Black-box knowledge distillation for large language models presents a strict trade-off. Simple off-policy methods (e.g., sequence-level knowle

Solving Physics Olympiad via Reinforcement Learning on Physics Simulators

arXiv:2604.11805v1 Announce Type: cross Abstract: We have witnessed remarkable advances in LLM reasoning capabilities with the advent of DeepSeek-R1. However, much of this progress has been fueled by

Soon, at each gradual improvement level of AI, you will start to see large discrete jumps in ability in economically important areas, becaus…

model-releasesethan-mollick--x

Soon, at each gradual improvement level of AI, you will start to see large discrete jumps in ability in economically important areas, because the previous AI ability level in some aspect of the job bo

Source: Anthropic is preparing to release Claude Opus 4.7, along with a new AI-powered tool for designing websites and presentations, as soon as this week (Stephanie Palazzolo/The Information)

Stephanie Palazzolo / The Information: Source: Anthropic is preparing to release Claude Opus 4.7, along with a new AI-powered tool for designing websites and presentations, as soon as this week — Anth

model-releasestechmeme

Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban (Politico)

Politico: Sources: at least two US federal agencies and three congressional committees have reached out to Anthropic to test Claude Mythos, quietly bypassing Trump's ban — The Commerce Department's Ce

model-releasestechmeme

Spatial Competence Benchmark

arXiv:2604.09594v1 Announce Type: new Abstract: Spatial competence is the quality of maintaining a consistent internal representation of an environment and using it to infer discrete structure and pla

SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence

arXiv:2505.17012v3 Announce Type: replace-cross Abstract: Existing evaluations of multimodal large language models (MLLMs) on spatial intelligence are typically fragmented and limited in scope. In thi

SpecMoE: A Fast and Efficient Mixture-of-Experts Inference via Self-Assisted Speculative Decoding

arXiv:2604.10152v1 Announce Type: new Abstract: The Mixture-of-Experts (MoE) architecture has emerged as a promising approach to mitigate the rising computational costs of large language models (LLMs)

SPEED-Bench: A Unified and Diverse Benchmark for Speculative Decoding

arXiv:2604.09557v1 Announce Type: cross Abstract: Speculative Decoding (SD) has emerged as a critical technique for accelerating Large Language Model (LLM) inference. Unlike deterministic system optim

Spoiler Alert: Narrative Forecasting as a Metric for Tension in LLM Storytelling

arXiv:2604.09854v1 Announce Type: new Abstract: LLMs have so far failed both to generate consistently compelling stories and to recognize this failure--on the leading creative-writing benchmark (EQ-Be

SRBench: A Comprehensive Benchmark for Sequential Recommendation with Large Language Models

arXiv:2604.09553v1 Announce Type: cross Abstract: LLM development has aroused great interest in Sequential Recommendation (SR) applications. However, comprehensive evaluation of SR models remains lack

StableTTA: Training-Free Test-Time Adaptation that Improves Model Accuracy on ImageNet1K to 96%

arXiv:2604.04552v2 Announce Type: replace-cross Abstract: Ensemble methods are widely used to improve predictive performance, but their effectiveness often comes at the cost of increased memory usage

STaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction

arXiv:2604.09737v1 Announce Type: cross Abstract: Structured prediction requires models to generate ontology-constrained labels, grounded evidence, and valid structure under ambiguity, label skew, and

STARS: Skill-Triggered Audit for Request-Conditioned Invocation Safety in Agent Systems

arXiv:2604.10286v1 Announce Type: new Abstract: Autonomous language-model agents increasingly rely on installable skills and tools to complete user tasks. Static skill auditing can expose capability s

StarVLA-alpha: Reducing Complexity in Vision-Language-Action Systems

arXiv:2604.11757v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for building general-purpose robotic agents. However, the VLA landsc

STORM: End-to-End Referring Multi-Object Tracking in Videos

arXiv:2604.10527v1 Announce Type: cross Abstract: Referring multi-object tracking (RMOT) is a task of associating all the objects in a video that semantically match with given textual queries or refer

StyleBench: Evaluating thinking styles in Large Language Models

arXiv:2509.20868v2 Announce Type: replace-cross Abstract: Structured reasoning can improve the inference performance of large language models (LLMs), but it also introduces computational cost and cont

Sub-32B open weights models now offer GPT-5 level intelligence with Qwen3.5 27B (Reasoning) matching GPT-5 (medium) at 42 and Gemma 4 31B (R…

model-releasesclem-delangue--x

Sub-32B open weights models now offer GPT-5 level intelligence with Qwen3.5 27B (Reasoning) matching GPT-5 (medium) at 42 and Gemma 4 31B (Reasoning) matching GPT-5 (low) at 39 on the Artificial Analy

Switch-JustDance: Benchmarking Whole Body Motion Tracking Controllers Using a Commercial Console Game

arXiv:2511.17925v3 Announce Type: replace-cross Abstract: Recent advances in whole-body robot control have enabled humanoid and legged robots to perform increasingly agile and coordinated motions. How

SymphoMotion: Joint Control of Camera Motion and Object Dynamics for Coherent Video Generation

arXiv:2604.03723v2 Announce Type: replace Abstract: Controlling both camera motion and object dynamics is essential for coherent and expressive video generation, yet current methods typically handle o

Synthius-Mem: Brain-Inspired Hallucination-Resistant Persona Memory Achieving 94.4% Memory Accuracy and 99.6% Adversarial Robustness on LoCoMo

arXiv:2604.11563v1 Announce Type: cross Abstract: Providing AI agents with reliable long-term memory that does not hallucinate remains an open problem. Current approaches to memory for LLM agents -- s

TAG-Head: Time-Aligned Graph Head for Plug-and-Play Fine-grained Action Recognition

arXiv:2604.11498v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) is challenging because visually similar actions differ by subtle spatio-temporal cues. Many recent systems

Tail-Aware Information-Theoretic Generalization for RLHF and SGLD

arXiv:2604.10727v1 Announce Type: cross Abstract: Classical information-theoretic generalization bounds typically control the generalization gap through KL-based mutual information and therefore rely

Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation

arXiv:2604.10720v1 Announce Type: new Abstract: Artificial models that simulate how learners act and respond within educational systems are a promising tool for evaluating tutoring strategies and feed

Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings

arXiv:2305.14299v3 Announce Type: replace-cross Abstract: Learning high quality sentence embeddings from dialogues has drawn increasing attentions as it is essential to solve a variety of dialogue-ori

TempusBench: An Evaluation Framework for Time-Series Forecasting

arXiv:2604.11529v1 Announce Type: new Abstract: Foundation models have transformed natural language processing and computer vision, and a rapidly growing literature on time-series foundation models (T

Text-to-Image Models and Their Representation of People from Different Nationalities Engaging in Activities

arXiv:2504.06313v5 Announce Type: replace Abstract: This paper investigates how popular text-to-image (T2I) models, DALL-E 3 and Gemini 3 Pro Preview, depict people from 206 nationalities when prompte

The Amazing Agent Race: Strong Tool Users, Weak Navigators

arXiv:2604.10261v1 Announce Type: new Abstract: Existing tool-use benchmarks for LLM agents are overwhelmingly linear: our analysis of six benchmarks shows 55 to 100% of instances are simple chains of

The Blind Spot of Agent Safety: How Benign User Instructions Expose Critical Vulnerabilities in Computer-Use Agents

arXiv:2604.10577v1 Announce Type: cross Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automat

The LLM tunes its own llama.cpp flags (+54% tok/s on Qwen3.5-27B)

This r/ollama post describes a technique where an LLM is used to automatically tune its own llama.cpp runtime flags — such as parameters related to GPU offloading, KV cache quantization, batch sizes,

model-releasesr-ollama

The Missing Knowledge Layer in Cognitive Architectures for AI Agents

arXiv:2604.11364v1 Announce Type: new Abstract: The two most influential cognitive architecture frameworks for AI agents, CoALA [21] and JEPA [12], both lack an explicit Knowledge layer with its own p

The Phase Is the Gradient: Equilibrium Propagation for Frequency Learning in Kuramoto Networks

arXiv:2604.10272v1 Announce Type: new Abstract: We prove that in a coupled Kuramoto oscillator network at stable equilibrium, the physical phase displacement under weak output nudging is the gradient

The Rise and Fall of G in AGI

arXiv:2604.09911v1 Announce Type: cross Abstract: In the psychological literature the term `general intelligence' describes correlations between abilities and not simply the number of abilities. This

The Salami Slicing Threat: Exploiting Cumulative Risks in LLM Systems

arXiv:2604.11309v1 Announce Type: cross Abstract: Large Language Models (LLMs) face prominent security risks from jailbreaking, a practice that manipulates models to bypass built-in security constrain

THEIA: Learning Complete Kleene Three-Valued Logic in a Pure-Neural Modular Architecture

arXiv:2604.11284v1 Announce Type: cross Abstract: We present THEIA, a modular neural architecture that learns complete Kleene three-valued logic (K3) end-to-end without any external symbolic solver, a

There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to ad…

model-releasesallie-k--miller--x

There are multiple realities of AI right now. And what you have access to drastically changes your workflows, trust in AI, and ability to adapt to the future. Here’s the briefest state of the AI world

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

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

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