model releases

Beyond Endpoint Performance: Process-Level Evaluation of Self-Evolving Agents

arXiv:2609.24663v1 Announce Type: new Abstract: Self-evolving agents convert interaction feedback into persistent artifacts, such as memories or skills, which in turn guide subsequent decisions. As th

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Beyond Short Segments : Expanding Speaker Embeddings with Vector Archives

DGX agent

arXiv:2609.25007v1 Announce Type: cross Abstract: The performance of state-of-the-art speaker verification (SV) systems severely degrades on short utterances due to insufficient speaker-specific infor

model-releasesarxiv-cs-cl

23 Sept 2026

Beyond Static Charts: Can Language and Vision Language Models Generate Interactive Data Visualization Interfaces?

arXiv:2609.26208v1 Announce Type: new Abstract: Data visualization is central to analytical reasoning, but real-world analysis increasingly requires language-driven interactive interfaces rather than

BigO(Bench): Can LLMs Generate Code with Controlled Time and Space Complexity?

arXiv:2503.15242v3 Announce Type: replace Abstract: We introduce BigO(Bench), a novel coding benchmark designed to evaluate the capabilities of generative language models in understanding and generati

Block-Level Weight-Space Structure Persists Under Post-Training: An Empirical Study Across LLM Families

arXiv:2609.26147v1 Announce Type: new Abstract: Modern LLMs are deployed as families of post-trained variants (base, instruct, chat, code) derived from a shared set of pre-trained weights. We present

Building Trustworthy Mental Health Benchmarks on Bluesky: A Validation-Aware Weak-Supervision Framework

arXiv:2609.22696v1 Announce Type: new Abstract: Decentralized social media platforms create new opportunities and challenges for computational mental health research because data access, moderation, l

C2FXNet: Coarse-to-Fine Scene Expert for Unified Object Detection across Adverse Weather

model-releasesarxiv-cs-cv

arXiv:2609.25693v1 Announce Type: new Abstract: Object detection in adverse weather remains challenging because severe degradations weaken visual quality and disrupt semantic feature representations a

CableVLA: Simulation-Privileged Global-Local Representation Learning for Cable Routing

model-releasesarxiv-cs-ro

arXiv:2609.25606v1 Announce Type: new Abstract: Cable routing requires coordinated control of global cable topology and changing local contacts. We present CableVLA, an end-to-end multimodal vision-la

CacheDyG: Decoupling Temporal Propagation for Efficient Dynamic Graph Learning

arXiv:2609.25814v1 Announce Type: new Abstract: Dynamic graphs are widely used to model time-evolving relational systems in real-world applications. Dynamic graph neural networks provide an effective

Calibration Count Reuse: Validity Does Not Determine Efficiency

arXiv:2609.25138v1 Announce Type: cross Abstract: Calibration count reuse raises separate validity and efficiency questions. We give a validity criterion for general count-dependent nonconformity scor

Can You Delete a Year of Market Data? Machine Unlearning Against Exact Retraining Oracles

arXiv:2609.26242v1 Announce Type: new Abstract: When a data license expires, deleting stored records does not remove influence encoded in a trained forecaster. Machine unlearning seeks to remove this

Can you take the cheapest open model from a frontier lab & beat closed models on the hardest long range tasks? Yep Our open adaptive intelli…

model-releasesemad-mostaque--x

Can you take the cheapest open model from a frontier lab & beat closed models on the hardest long range tasks? Yep Our open adaptive intelligence system Zenith ramps DeepSeek v4.1 Flash past GPT 5.6 S

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

arXiv:2609.26637v1 Announce Type: new Abstract: The rapid capability gains of frontier language models are widely attributed to improved reasoning abilities, yet this cannot be verified as raw CoT tra

Certified Against Which Oracle? Execution Labels Set the Reported Risk of Conformal Abstention for Text-to-SQL

arXiv:2609.25938v1 Announce Type: cross Abstract: A conformal abstention certificate for text-to-SQL is only as truthful as the correctness labels it is calibrated on. The uncertainty pipelines that r

ChainDoRA: Tensor-Train Factorized Weight-Decomposed Low-Rank Adaptation for Parameter-Efficient LLM Fine-Tuning

arXiv:2609.25058v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) adapts large language models (LLMs) to downstream tasks while updating only a small fraction of their pretrained

ChemVTS-Bench: Evaluating Visual-Textual-Symbolic Reasoning of Multimodal Large Language Models in Chemistry

arXiv:2511.17909v2 Announce Type: replace Abstract: Chemical reasoning inherently integrates visual, textual, and symbolic modalities, yet existing benchmarks rarely capture this complexity, often rel

CivBench: Progress-Based Evaluation for LLMs' Strategic Decision-Making in Civilization V

arXiv:2604.07733v2 Announce Type: replace Abstract: Evaluating strategic decision-making in LLM-based agents requires generative, competitive, and longitudinal environments, yet few benchmarks provide

Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of …

model-releasesboris-cherny--x

Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRI

CliffCompaction: Cost-Efficient Compaction for Long-Horizon Coding Agents

arXiv:2609.26779v1 Announce Type: cross Abstract: Agents often work on complex problems that require millions of tokens of context, which necessitates compacting across sessions due to limited context

Combinatorial Network-Based Manifold Topological Deep Learning for Image Analysis

model-releasesarxiv-cs-cv

arXiv:2609.25453v1 Announce Type: new Abstract: Medical image analysis remains fundamentally challenging because of the intricate geometric and topological structures present in medical data. Conventi

Combining Hierarchical Cognitive Process with Process Supervision for Interpretable Scene Safety Understanding

arXiv:2609.26399v1 Announce Type: new Abstract: Scene safety understanding plays a life-or-death role in situational awareness in various critical domains. Traditional methods that rely on learning di

Compared to What? A Human-Anchored Security Benchmark for LLM-Generated Infrastructure-as-Code

arXiv:2608.28021v2 Announce Type: replace-cross Abstract: Large language models increasingly author Infrastructure-as-Code (IaC), where one insecure default is provisioned straight into production. Pr

Component Type, Not Reconstruction Error, Predicts Attention Quantization Sensitivity

arXiv:2609.26173v1 Announce Type: new Abstract: Many post-training quantization (PTQ) methods use layer-wise reconstruction, second-order proxy objectives, or activation-aware transformations to reduc

Compressing Long Context into Answer-Aligned Memory Embeddings for LLM Inference

arXiv:2609.25537v1 Announce Type: new Abstract: Large language model (LLM) inference is constrained by the quadratic scaling of self-attention and the linear scaling of the KV cache, increasing latenc

Construting Reverse Thinking: Developing Large Language Models' Reverse Thingking Ability

arXiv:2609.24760v1 Announce Type: new Abstract: When facing complex problems, humans tend to try various ideas for different issues. Human thinking patterns exhibit remarkable flexibility in adapting

Controlling risks of AI in chemical science with agents

arXiv:2312.06632v2 Announce Type: replace Abstract: Artificial intelligence is rapidly advancing scientific discovery, but this progress carries risks of misuse, such as the creation of harmful substa

Correcting Within-Group Self-Selection Bias in Prioritized Replay

arXiv:2609.25297v1 Announce Type: new Abstract: Prioritized experience replay (PER) improves sample efficiency by replaying high-priority transitions, usually according to absolute temporal-difference

CoVeR: Coverage-Based Routing of Verifier Calls in Agentic Retrieval

arXiv:2609.26086v1 Announce Type: new Abstract: An agentic retrieval system issues a sequence of search queries and must decide, at each step, whether the evidence collected so far is enough to stop.

CraftBench-UE: Deterministic Evaluation for Coding Agents in Unreal Engine

arXiv:2609.23142v1 Announce Type: new Abstract: Building gameplay features in a game engine requires more than code, as code that compiles and runs does not necessarily implement the requested gamepla

Custom Node for Extract Prompt & Target Aspect Ratio/Dimensions from Qwen Image 2.1 PE

model-releasesr-stablediffusion

Hey everyone! I've been experimenting with Qwen Image 2.1 Prompt Enhancer (PE) lately and noticed an interesting detail in Qwen's official system prompts. The PE models output structured JSON containi

DeceptionAnalyser: A Web-Based AI Tool for Performing Structured Deception Analysis with Argumentation Schemes and LLMs

arXiv:2609.24369v1 Announce Type: cross Abstract: Deception plays a central role in Intelligence operations, yet it remains difficult to analyse systematically without expert knowledge of reasoning pa

Deep Generative Crystal Structure Prediction: A Benchmark Study and a Controlled Test of Prototype Dependence

arXiv:2609.26502v1 Announce Type: cross Abstract: Deep generative models are widely reported to enable de novo crystal structure prediction (CSP), but their capability has not been measured consistent

Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing

arXiv:2609.25397v1 Announce Type: new Abstract: The one-dimensional bin packing problem (1D-BPP) is a classical NP-hard combinatorial optimization problem with applications ranging from logistics and

DeepSeek and Moonshot AI face Beijing's probe over potential data leaks to Anthropic

model-releasesr-localllama

The rumor about Kimi execs getting arrested finally has some legs. I believe the reality is more like under investigation for potential arrests or fine. submitted by /u/Ok_Warning2146 [link] [comments

Diffusion Drafts, AR Verifies: Accelerating Document OCR with Self-Speculative Decoding

arXiv:2609.26638v1 Announce Type: new Abstract: Autoregressive OCR vision-language models accurately convert document images into text and structured markup, but require one sequential decoding step p

Diffusion-Induced Spatial Attention Overlapping Community Detection

arXiv:2609.26737v1 Announce Type: cross Abstract: Detection of overlapping communities is essential for modelling networks in which nodes participate simultaneously in multiple structural or functiona

Directional Total Variation-Regularized Implicit Neural Representations (DTV-INR) for Continuous Super-Resolution in Degraded Imaging Domains

model-releasesarxiv-cs-cv

arXiv:2609.25429v1 Announce Type: new Abstract: In this paper, we introduce the Directional Total Variation-Regularized Implicit Neural Representation (DTV-INR), an advanced variational paradigm that

Disaggregated Quantization: Specializing LLM Prefill and Decode

arXiv:2609.26333v1 Announce Type: new Abstract: Prefill and decode reward different approaches to quantization: low-precision arithmetic accelerates prompt processing, while compact weights reduce mem

Discrete vs. Continuous: A Comprehensive Study of Unified Audio Understanding in LALMs

arXiv:2609.22851v2 Announce Type: cross Abstract: Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio u

Do Not Trust the Benchmark: Limitations of General LLM Rankings and a Case for Task-Specific Evaluation

arXiv:2609.23201v1 Announce Type: new Abstract: Benchmark scores increasingly influence the development, marketing, and selection of large language models (LLMs). Yet an overall score is interpretable

Do Synthetic Personas Predict Real Audience Response? A Sim-to-Real Study Where a No-Persona Baseline Beats Persona-Based Copy Simulation

arXiv:2609.25010v1 Announce Type: cross Abstract: Marketers increasingly use large language models (LLMs) as 'synthetic personas' to predict how an audience will react to a piece of copy before it shi

DocMIDE: Learning Multi-Hop Implicit Derivation in Visually Rich Documents

arXiv:2609.24092v1 Announce Type: new Abstract: Real-world document processing systems rely on rigid, predefined schemas, yet critical target fields often lack direct visual counterparts on the page.

Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Mining

arXiv:2609.26034v1 Announce Type: new Abstract: Water treatment research is expanding rapidly, but much of the knowledge acquired from this research remains scattered across unstructured literature. T

DreamStream: Towards Policy-Oriented Generative Simulation for End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2609.26792v1 Announce Type: new Abstract: Faithfully evaluating end-to-end driving policies in simulation requires observations that are not merely photo-realistic, but preserve the scene featur

DTOC: Dynamic Tool Output Compression for Adaptive Context Management in AI Agents

arXiv:2609.26121v1 Announce Type: cross Abstract: As agent capabilities have grown, practical limitations increasingly stem from constrained context windows rather than model capacity. Common strategi

Dual-GNN Multilevel Coarsening for Maximum Independent Set

arXiv:2609.25149v1 Announce Type: new Abstract: Solving large-scale instances of the Traveling Salesman Problem (TSP) exactly is computationally expensive. Researchers often employ graph sparsificatio

DUMA-Bench: A Dual-Control Multi-Agent Benchmark for Evaluating LLM Agent Security

arXiv:2609.24662v1 Announce Type: new Abstract: LLM-based agents increasingly operate in environments where they interact with users, tools, and external systems. Yet most security evaluations assume

DVA-Neurons: Design and Verification of Adaptive LIF Neurons: From Single-Neuron Dynamics to Multi-Neuron Spiking Networks

arXiv:2609.22775v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer a promising path toward ultra-low-power artificial intelligence inference by emulating the event-driven computation