Search: “benchmark”

Post-Reasoning: Improving the Performance of Non-Thinking Models at No Cost

arXiv:2605.06165v2 Announce Type: replace Abstract: As the widespread adoption of Large Language Models (LLMs) accelerates, token consumption from intermediate reasoning traces increasingly contribute

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Pretraining for Sample-Efficient Neural Interfaces

DGX agent

arXiv:2609.13507v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) decode neural activity to restore lost function. Typically, training a high-performance neural decoder requires a large

model-releasesarxiv-cs-lg

15 Sept 2026

Query-Conditioned Spherical Centroid Aggregation for Multimodal Retrieval

arXiv:2609.15335v1 Announce Type: new Abstract: Multimodal retrieval integrates video, audio, subtitles, and text; however, recent geometric aggregators, such as Gramian volumes, hyperbolic volumes, a

Qwen3.8 27B with embeddings

As you know, Qwen3.8 27B has built-in support for embeddings. It gives pretty decent results in llama.cpp with the following parameters: --embedding --pooling mean The problem is that enabling embeddi

Semantic-TVM: Structure-Preserving Trustworthy Virtual Memory for Memory-Augmented and Tool-Using Agents

arXiv:2609.15011v1 Announce Type: new Abstract: Memory-augmented and tool-using agents expose exact private values when remote LLMs process retrieved memory, tool actions, and intermediate observation

SpermYOLO: A Coordinated YOLO-Based Detector for Accurate and Efficient Sperm and Impurity Detection in Microscopic Images

arXiv:2609.14278v1 Announce Type: cross Abstract: Accurate sperm detection is essential for computer-assisted semen analysis, yet it remains challenging in microscopic images due to dense distribution

SpliTEE: Improving LLM Inference on Trusted Hardware with Differentially Private GPU Outsourcing

arXiv:2609.15039v1 Announce Type: cross Abstract: User prompts provided to large language models (LLMs) may contain sensitive or private information that can be misused by remotely deployed models, su

Structure-Token Evidence-Anchored Reasoning for Scientific Chart Understanding

arXiv:2609.13267v1 Announce Type: new Abstract: Scientific charts encode quantities in axes, legends, and geometric marks, yet large vision-language models still treat them as natural photographs. Vis

Syn2Logic: End-to-End Neuromorphic Design Automation

arXiv:2608.25536v2 Announce Type: replace-cross Abstract: In this work, we propose a view on electronic Neuromorphic Design Automation (eNDA), which we see as a design automation flow that bridges com

The average-farmer illusion in language-model simulations of agricultural decisions

arXiv:2609.15038v1 Announce Type: new Abstract: Language-model agents are increasingly used as synthetic people in surveys and social simulations, yet their apparent realism is often judged from popul

Research

The Garden of Forking Prompts: How Users Explore Narrative Space in Story Generation

arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate storie

researcharxiv-cs-cl

The Troy Moment of AI: Why SomeWill Cheat and SomeWill Follow?

arXiv:2609.15494v1 Announce Type: new Abstract: Recent investigations of the July 2026 OpenAI--Hugging Face incident motivate two questions about agent behavior under task failure: when an assigned ta

Tool Use Reduces Depth-Induced Collapse in OOD Reasoning

arXiv:2602.21061v2 Announce Type: replace Abstract: Many current paths to more advanced AI depend on the assumption that large language models (LLMs) can generalize learned relationships to solve comp

TypiCore: A Hybrid Active Query Strategy for Class-Incremental Learning on Time Series

arXiv:2607.17632v2 Announce Type: replace-cross Abstract: Time series data play a pivotal role across numerous domains, including healthcare and manufacturing. In real-world environments, models must

VisInteract: Towards Dynamic Interactive Text-to-Visualization under Imperfect Queries

arXiv:2609.15182v1 Announce Type: new Abstract: Real-world visualization requests are routinely ambiguous, incomplete, or factually incorrect, yet existing Text-to-Visualization (Text-to-Vis) systems

Voodoo Dynamic Quant - Now MIT Licensed

Two months ago I announced I had found a new dynamic quant method called Voodoo Quant which was SOTA for the most aggressive quant levels on some smaller Qwen3.5 GGUF models. I kept the methodology pr

Research

When the Wrong Key Wins: Understanding and Detecting Hallucinations in LLMs

arXiv:2609.15106v1 Announce Type: new Abstract: Large language models can hallucinate even when the knowledge required for a correct answer is already available. We study this failure through a latent

researcharxiv-cs-cl

AnyView: Synthesizing Any Novel View in Dynamic Scenes

arXiv:2601.16982v2 Announce Type: replace Abstract: Modern generative video models excel at producing convincing, high-quality outputs, but struggle to maintain multi-view and spatiotemporal consisten

AquaCubeAI-Powered Monitoring Turbidity on-board {Phi}sat-2

arXiv:2609.12744v1 Announce Type: new Abstract: Timely monitoring of coastal water quality is critical for environmental protection, yet conventional satellite workflows rely on downlink and ground pr

Automated Detection and Structuring of Social Tipping Point Evidence in Climate related Documents: A Modular AI Framework

arXiv:2609.12254v1 Announce Type: new Abstract: The climate literature has grown faster than review teams can read it. That gap matters most for a concept like the environmental social tipping point,

Do LLMs Trust the Accuser or the Accusation? Measuring Belief Shifts in Werewolf

arXiv:2609.12446v1 Announce Type: cross Abstract: Social-deduction games such as Werewolf are increasingly used to evaluate LLM agents, but existing evaluations often rely on final game outcomes. We p

Extracting Dataset Mentions in Forced Displacement and FCV Documents: A Weakly Supervised Framework with LLM-Based Label Refinement

arXiv:2609.12107v1 Announce Type: new Abstract: Development and humanitarian organizations produce and support surveys, administrative registries, and other data resources to inform research, policy,

Agents

GAUGE: When Not to Trust LLM-as-a-Judge in User-Simulated Evaluation of Task-Oriented Agents

arXiv:2609.12191v1 Announce Type: new Abstract: Comparing and selecting task-oriented LLM agents increasingly relies on a low-cost offline evaluation gate: persona-driven LLM user-simulators converse

agentsarxiv-cs-cl

Generative Retrieval for Unsupervised Text-Based Person Search

arXiv:2609.12965v1 Announce Type: new Abstract: Text-based person search (TBPS) aims to retrieve images of a target person from a large image gallery based on a given natural language description. Mos

Input Resolution Matters: Real-Time Object Detection Latency

arXiv:2609.12920v1 Announce Type: new Abstract: We model total latency as the convolution of preprocessing, inference, and postprocessing distributions under a simplifying independence approximation,

LGFN: Lightweight Gated RGB-Polarization Fusion with Modality-Availability Conditioning for Camouflaged Object Detection

arXiv:2609.12798v1 Announce Type: new Abstract: Camouflaged object detection (COD) is an important engineering task in intelligent optical perception, but it remains challenging when targets closely r

Limits of LLM Text Detectors in Education

arXiv:2508.08096v2 Announce Type: replace Abstract: Students increasingly use the assistance of large language models (LLMs) in their academic writing. While slight assistance (e.g., grammar and style

LLM Compression by Block Removal with Constrained Binary Optimization

arXiv:2602.00161v3 Announce Type: replace-cross Abstract: In this paper, we formulate the compression of large language models (LLMs) by optimally deleting transformer blocks (``block removal'') as a

Look Before You Leap: Pre-Action Verification for LLM Agents

model-releasesarxiv-cs-lg

arXiv:2609.11957v1 Announce Type: new Abstract: An LLM agent acts on the world by emitting actions: shell commands to run, edits to apply. A wrong action does not always fail loudly; it can fail silen

RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs

arXiv:2609.12552v1 Announce Type: new Abstract: Open-vocabulary detection accepts any class list at inference, and promptable segmentation returns regions without class names: the taxonomy has left th

Unified Text-Image Generation with Weakness-Targeted Post-Training

arXiv:2601.04339v3 Announce Type: replace Abstract: Unified multimodal generation architectures that jointly produce text and images have recently emerged as a promising direction for text-to-image (T

Hoping for Optimized Smarter Upcoming Models .... Like DeepSeek-V4.1-Flash( KVCache + Engram) in Small/Medium/Big sizes

It's still a dream for many folks to run medium size(30B range) models @ Q8 with Unquantized KVCache (256K Context) on their GPUs. It would be awesome to have DeepSeek-V4.1-Flash's KVCache + Engram fo

Horse racing as an ML ranking problem: 1.18M runners, walk-forward validation and a very strong market baseline [D]

model-releasesr-machinelearning

Hi 👋 long time lurker It’s been a few years since the last post about Horse Racing within this sub. A few years ago I was reading a popular science book and came across the story Bill Benter and the s

ROCm 7.2.1 + llama.cpp on mixed Vega GPUs (gfx900 Vega64 + gfx906 MI50) — got 52-57 tok/s on Gemma 3 27B Q4 with patched rocBLAS payloads [repo + Dockerfile]

I'm documenting a reproducible setup for running current llama.cpp on a mixed AMD Vega system with both: Radeon RX Vega 64 / Vega10 / gfx900 (8GB HBM2) Radeon Instinct MI50 (Vega20) / gfx906 (16GB HBM

model-releasesr-ollama

try deepseek v4.1 flash now on together ai: https://www.together.ai/models/deepseek-v4-1-flash

model-releasestogether-ai--x

DeepSeek V4.1 Flash is now available on Together AI’s model hub (https://www.together.ai/models/deepseek-v4-1-flash). The release includes the DeepSeek V4.1 Flash API with updated pricing, performance

3.8-27B has ruined 3.5/3.6-35B’s for me. It’s just absurdly superior.

Applied science work, from workflow design, data pipeline, results analysis, article/reports writing and data publishing online. 5 projects I did in the past replicated from start to finish. 3x to 4x

52 knobs, 72 hours, one compiled Rust model: Catalyst told an AI agent what actually mattered in 1.37s and verified every answer

I’ve been building Catalyst around a capability I want engineering agents to have: An AI agent can read a program and make a good guess about what matters. Catalyst lets it measure what actually matte

model-releasesr-ollama

Research

Calibration-Aware Uncertainty Cascades for Efficient Heterogeneous Model Collaboration

arXiv:2609.11446v1 Announce Type: new Abstract: Heterogeneous model collaboration seeks to exploit the complementary strengths of different models to balance predictive performance and inference cost.

researcharxiv-cs-ai

Deepseek v4.1 Flash Peak Rates… why?

Can someone explain to me why Ollama Cloud are billing with same peak/off peak windows as Deepseek since they are hosting the model across US/EU infrastructure? submitted by /u/veganmaister [link] [co

model-releasesr-ollama

For those of you forced to only use open models from Western labs in production, what are you deploying?

First off, I know that GLM, Qwen, and DeepSeek absolutely dominate in terms of SOTA Open Source models, and that’s what I use in my personal projects and for school, however, I’m also responsible for

I am impressed and I owe you one, Qwen 3.8 flash next (vision)!

I have enabled the vision for the CIRU Strix UL4 quant of Qwen 3.8 flash next (others quants likely perform very similar) and tried it on a few things, then wanted to show my partner how great it work

Probabilistic Focal Search: Accelerating Bounded-Suboptimal Search via Lower-Bound Advancement

arXiv:2609.10584v1 Announce Type: new Abstract: Bounded-suboptimal search seeks a solution within a factor w of optimal while reducing search effort. Focal Search (FS) uses heuristic guidance within F

This draft model is OP on 16 GB cards for Qwen 3.8 27b

https://huggingface.co/HermiHg/Qwen3.8-27B-DFlash2-Q2_K_S-MIX-GGUF I used this draft model with https://huggingface.co/ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF with the IQ3_XXS with 128k context and I saw

What pi.dev plugin do you suggest for context, compaction and memory management of local models?

I have been battling with my Qwen3.8:27b setup on my rtx 5080 16gb. I am using llama.cpp to run a nvfp4 version of qwen3.8:27b llama-b10699-bin-win-cuda-13.3-x64llama-server.exe -hf williamliao/Qwen3.

Safety

X-AuT: Progressive Audio-Encoder Compression for Speech LLMs with Cross-Scale Distillation

arXiv:2609.11412v1 Announce Type: cross Abstract: Reducing audio-encoder depth lowers the inference cost of speech large language models, but removing complete blocks perturbs the embeddings consumed

safetyarxiv-cs-ai

A Fragility Spectrum for Recursive Language-Model Training

arXiv:2609.11149v1 Announce Type: new Abstract: Model-generated text is finding its way back into training corpora, and there is plenty of evidence that training on such data over and over collapses o

11 Sept 2026

A Training-Free, Alignment-Free Approach to Corporate Intelligence: Application to SEC Filings

arXiv:2609.11620v1 Announce Type: new Abstract: High-dimensional dense text embeddings and large language models face real obstacles in financial-disclosure analysis: context-window limits, hallucinat

11 Sept 2026

agreed, one of the biggest bottlenecks right now is my own ability to internalize the information that these models convey the latest models…