Search: “model-releases”

PuzzleKV: Page-Wise Low-Rank Decomposition for KV Cache Compression

arXiv:2608.23843v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is increasingly limited by the memory required for the key-value (KV) cache. KV cache compression

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

QABBA: Error-Guaranteed Symbolic Time-Series Compression via Integer-Quantized Aggregation

DGX agent

arXiv:2411.15209v3 Announce Type: replace Abstract: The expansion of time-series data from sensors and monitoring systems has made compact representations increasingly important. Such representations

model-releasesarxiv-cs-lg

26 Aug 2026

QiMeng-ChipV-RTL: Exploiting Information Locality for IP-level Verilog Generation

arXiv:2602.00704v2 Announce Type: replace Abstract: The generation of Register-Transfer Level (RTL) code is a crucial yet labor-intensive step in digital hardware design, traditionally requiring engin

QML for Quantum Sensing under Measurement-Induced Information Loss

arXiv:2608.23934v1 Announce Type: cross Abstract: Nitrogen-vacancy (NV) centers in diamond can serve as highly sensitive solid-state quantum sensors for high-sensitivity magnetometry. However, in the

Qwen3.8-27B IQ3_XXS wrote a correct multilayer TMM on a 16 GB Quadro — after 100 minutes, 3 compactions, and 108k output tokens

model-releasesr-localllama

https://preview.redd.it/i8rjx0ar5mlh1.png?width=2160&format=png&auto=webp&s=c2588bc7b2519ea71b176ca73faf566dfc585496 I wanted to see whether a heavily quantized 27B model running entirely on an older

Qwen3.8-Flash-Next

model-releasessimon-willison

Qwen3.8-Flash-Next Another open weights model from Qwen. This one is 'a multimodal MoE model that also serves as an early preview of the architecture used in Qwen4'. It's pretty big: 125B tokens, but

RAGSentinel: Certifiable Geometric Consensus for Robust Retrieval-Augmented Generation

arXiv:2608.23965v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models by grounding responses in external documents, but it also expose

Recursive Agentic Reasoning

arXiv:2608.23956v1 Announce Type: new Abstract: Test-time reasoning methods such as iterative refinement, decomposition, and repeated sampling are often evaluated in isolation, making their gains diff

Recursive Experiential-Working Memory Evolution for Long-Horizon Agent Harnesses

arXiv:2608.24876v1 Announce Type: new Abstract: Recursive self-improvement (RSI) remains hard in long-horizon tasks, where growing histories obscure the task state and misalign skill invocation. We in

REFINE: A Multi-Agent LLM Approach for Evidence-Guided Code Refactoring

arXiv:2608.23611v1 Announce Type: cross Abstract: Large Language Models (LLMs) offer new opportunities for automated code refactoring. However, generated changes must reduce targeted quality problems

Relative Time Intervals Representation for Word-level Timestamping with Masked Training

arXiv:2608.24041v1 Announce Type: new Abstract: Although Speech Large Language Models (SpeechLLMs) excel at speech understanding and generation, their capacity for fine-grained, temporally aligned out

RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation

arXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a mem

ReproAgent: Contract-Guided Paper-to-Code Reproduction

arXiv:2608.24291v1 Announce Type: new Abstract: Paper-to-code reproduction asks scientific AI agents to turn research papers into executable repositories that preserve the paper's method, protocol and

Response Renormalization for Critical Deep Equilibrium Models

arXiv:2608.23725v1 Announce Type: new Abstract: Deep Equilibrium Models (DEQs) compute predictions from a hidden representation unchanged by the model update. Training through this equilibrium uses im

Restoring Without Forgetting: Continual Learning Across Image Degradations

arXiv:2608.23799v1 Announce Type: cross Abstract: Recent progress in image restoration has converged on all-in-one architectures that jointly handle multiple degradations within a single network. Thes

Revelation Control

arXiv:2608.23860v1 Announce Type: cross Abstract: Revelation Control is the problem of choosing priced interventions that reveal hidden state only insofar as the revealed distinctions can change a con

Robust Code RL via Faulty-Code-Driven Test case Synthesis and Dense Reward Shaping

arXiv:2608.24135v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has emerged as a pivotal technique for enhancing the code generation capabilities of Large Languag

Robust Motion Generation using Part-level Reliable Data from Videos

arXiv:2512.12703v2 Announce Type: replace-cross Abstract: Extracting human motion from large-scale web videos offers a scalable solution to the data scarcity issue in character animation. However, som

SA-Bench: Evaluating Semantic Alignment in LLM-Based Paper Reproduction

arXiv:2608.24252v1 Announce Type: new Abstract: LLM agents can generate paper reproduction code, yet often produce scientifically unfaithful implementations. We define this failure mode as semantic dr

SAGE: From Direct Answering to Evidence-Grounded Inference for Chinese Ancient Document Understanding

arXiv:2608.24011v1 Announce Type: cross Abstract: Chinese ancient document understanding demands complex visual, linguistic, and historical reasoning. Current Large Vision-Language Models (LVLMs) typi

Salesforce and Anthropic unveil Claudeforce, which brings Salesforce data and workflows into Claude, starting with a plugin featuring 37 prebuilt sales skills (Michael Nuñez/VentureBeat)

Michael Nuñez / VentureBeat: Salesforce and Anthropic unveil Claudeforce, which brings Salesforce data and workflows into Claude, starting with a plugin featuring 37 prebuilt sales skills — Salesforce

model-releasestechmeme

SandwichQuant: Which Parameters Matter Before and After Quantization?

arXiv:2608.24173v1 Announce Type: new Abstract: Quantization correction methods usually optimize weights, quantization parameters, or reconstruction objectives, while the underlying parameter subspace

Scalable and Versatile Identification for Hierarchical Structural Causal Models: A New Look at Project STAR

arXiv:2608.24500v1 Announce Type: cross Abstract: The STAR (Student-Teacher Achievement Ratio) experiment (1985, Tennessee, USA) is a landmark hierarchical dataset designed to assess the impact of cla

Segmentation-Guided Homography Estimation for Long-Term Planar Tracking

arXiv:2602.19624v2 Announce Type: replace Abstract: Recent state-of-the-art visual trackers produce high quality and long-term-stable segmentation masks. We propose to leverage these strengths for pla

SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning

arXiv:2608.24561v1 Announce Type: new Abstract: Rapid earthquake magnitude estimation is central to earthquake early warning, yet many operational systems depend on dense regional seismic networks and

Sensorless damage-safe grasping

model-releasesarxiv-cs-ro

arXiv:2608.23983v1 Announce Type: new Abstract: Robotic fruit harvesting must hold produce securely without bruising it, yet compression stiffness varies several-fold with ripeness within a single spe

SIREN-Bench: Behavior-Driven Generation and Evaluation of Emergency-Vehicle Interactions

model-releasesarxiv-cs-ro

arXiv:2608.24094v1 Announce Type: new Abstract: Emergency vehicles (EMVs) can reorganize surrounding traffic as civilian vehicles brake, change lanes, or form rescue corridors in response to their pas

SonarLLM: A Native Sonar--Optical Multimodal Large Language Model for Underwater Perception

arXiv:2608.24325v1 Announce Type: new Abstract: Reliable underwater perception requires complementary sensing under variable visibility. Optical cameras capture appearance and semantics but degrade ra

Source-Face Authenticity Detection for 3D Gaussian Heads Reconstructed from a Single Portrait: A Benchmark and Dedicated Detector

arXiv:2608.23984v1 Announce Type: new Abstract: Recent advances in single-image 3D Gaussian head reconstruction have enabled highly realistic and freely renderable digital heads from a single portrait

Spatial-DISE: A Unified Benchmark for Evaluating Spatial Reasoning in Vision-Language Models

arXiv:2510.13394v4 Announce Type: replace Abstract: Spatial reasoning ability is crucial for Vision Language Models (VLMs) to support real-world applications in diverse domains including robotics, aug

StarHarness: Evolving Harnesses with Stratified Search for Enterprise Environments

arXiv:2608.24804v1 Announce Type: new Abstract: We present StarHarness, a framework for evolving environment-specific agent harnesses while keeping model weights fixed. The evolved harness can include

StateTune: Transforming LLM-Assisted EDA Flow Tuning into a Stateful, Closed-Loop Process

arXiv:2608.23601v1 Announce Type: cross Abstract: EDA flow parameter tuning is critical for quality-of-results~(QoR), yet the parameter space is large, tightly coupled, and full evaluations are prohib

StepGuard: Learning Step-Level Guardrails with Scalable Supervision and Safety-Utility Balancing

arXiv:2608.24777v1 Announce Type: new Abstract: LLM-based agents can interact with external environments through tool invocation, but this capability also introduces security risks such as file modifi

Strictly Causal Streaming Video Anomaly Detection with a Theoretically-Grounded State-Space Core

arXiv:2608.24810v1 Announce Type: new Abstract: Recent work has applied Mamba style state space models (SSMs) to video anomaly detection, yet existing approaches still rely on buffering clips or windo

Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection

arXiv:2608.24113v1 Announce Type: cross Abstract: Time-series anomalies can appear not only as pointwise deviations but also as changes in recurring temporal structure, such as shifted periodicity or

Symbolic Classification-Enabled LHC Limits Online BSM Global Fits

arXiv:2605.22330v1 Announce Type: cross Abstract: Global fits of Beyond the Standard Model (BSM) physics often involve a two-way interplay between theory and experiment. Theoretical models provide gui

Syn2RealTrack: Bridging the Gap Between Synthetic and Real-World Datasets for Online Multi-View Multi-Target Tracking

arXiv:2608.24130v1 Announce Type: cross Abstract: Multi-camera 3D perception systems for warehouse scenes are trained largely on synthetic data and evaluated on physically captured environments. The r

Taming foundation model with invariance-oriented pre-training for broad-spectrum EEG analysis across signal-level, brain-state, and brain-health tasks

arXiv:2608.24597v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a widely used window into human brain function, but most EEG models remain tied to a one-dataset-one-model supervised

TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning

arXiv:2601.16520v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compo

The Empire, Long Divided, Must Unite: Architectural Convergence in Three LLM Agent Harnesses

arXiv:2608.23953v1 Announce Type: cross Abstract: An agent harness is what turns a language model into an autonomous agent: the surrounding code that builds the model's context, mediates its tools, ru

The Handoff Tax: Continuing Non-Native Trajectories in LLM Agents

arXiv:2608.24358v1 Announce Type: new Abstract: Coding agents perform long-running tasks spanning dozens of model calls, tool uses, and code edits. As these runs unfold, users face a practical cost-qu

The inside story on why OpenAI agents hacked Hugging Face

model-releasesmit-tech-review

The models responsible for last month’s agent hack of Hugging Face had been inadvertently trained to cheat and to communicate with each other, according to an OpenAI technical report released today. T

Today we’re introducing Gemini 3.5 Transcribe, our latest transcription model built for incredibly precise, smart dictation across your favo…

model-releasesgoogle-ai--x

Today we’re introducing Gemini 3.5 Transcribe, our latest transcription model built for incredibly precise, smart dictation across your favorite apps and devices. Remember when traditional speech-to-t

ToolRobustBench: Stage-Wise Perturbation Evaluation and Failure Diagnosis for Tool-Calling Agents

arXiv:2608.23635v1 Announce Type: cross Abstract: Large language models (LLMs) rely on tool calling as a fundamental agent capability, enabling them to invoke external systems and complete tasks beyon

TorchMorph: CUDA-accelerated Morphological Transforms

arXiv:2608.24738v1 Announce Type: new Abstract: Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e.

Towards Reliable AI-Based Histological Staining: A Systematic Study of Scaling and Uncertainty in Unpaired Generative Models

arXiv:2608.24626v1 Announce Type: new Abstract: Liver fibrosis, the principal predictor of long-term outcome in chronic liver disease, is staged from histological estimates of collagen content. Sirius

TRACE: An Evidence-Grounded Benchmark for Safety Evaluation of Large Reasoning Models

arXiv:2608.24232v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate intermediate reasoning traces that may contain unsafe content, even when their final responses appear safe. Guard

TrAct: Bridging Robot Control and Visual Prediction with Visual Tracks

model-releasesarxiv-cs-ro

arXiv:2608.24101v1 Announce Type: new Abstract: Robot actions are inherently embodiment-specific and only weakly aligned with image-space visual changes, limiting their effectiveness as conditioning s