Text understanding and language tasks
BANKING77 (77 fine-grained banking intents) is a well-established but increasingly saturated intent classification benchmark. did this wh...
94.42% Accuracy on Banking77 Official Test Split BANKING77-77 is deceptively hard: 77 fine-grained banking intents, noisy real-world quer...
Hi everyone, I'm currently in the evaluation phase of my Final Year Project and am looking for feedback on the system I've built. It's ca...
![[2602.13235] Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper introduces Lang2Act, a novel framework for enhancing visual reasoning in Vision-Language Models (VLMs) through self-emergent li...
NL2LOGIC presents a novel framework for translating natural language into first-order logic using large language models, enhancing accura...
This paper presents VaryBalance, a novel framework for detecting text generated by large language models (LLMs), outperforming existing m...
This article presents a geometric taxonomy of hallucinations in large language models (LLMs), categorizing them into three types: unfaith...
The paper presents AMOR, an entropy-based metacognitive gate that enhances attention switching in state space models, improving efficienc...
The article discusses how AI is revolutionizing document processing and PDF workflows, highlighting advancements in automation, accuracy,...
This article discusses the use of linear RNNs for state-tracking tasks, particularly focusing on permutation composition and its implicat...
This article explores how transformers process indexical language, focusing on self-reference circuits and their implications for underst...
The article discusses the submission and review process for short papers in machine learning, focusing on the unique challenges and expec...
Izwi has released significant updates, including local speaker diarization, forced alignment for accurate timestamps, and real-time strea...
The article discusses the current hype surrounding AI note-taking apps, questioning their effectiveness in real-world scenarios compared ...
The paper presents T3D, a framework for enhancing few-step diffusion language models through trajectory self-distillation and direct disc...
This article explores the effectiveness of agentic theorem provers through a statistical provability theory, analyzing their performance ...
The paper introduces Reinforced Attention Learning (RAL), a novel framework that optimizes internal attention distributions in multimodal...
The paper presents HEART, a framework that leverages emotional cues to enhance the reasoning capabilities of language models during test-...
The paper presents Highlight & Summarize (H&S), a novel design pattern for retrieval-augmented generation (RAG) systems that prevents jai...
This article presents a novel approach to uncertainty estimation in vision-language models (VLMs) by proposing a post-hoc method that enh...
The paper introduces Minmax Trend Filtering (MTF), a novel approach to Total Variation Denoising (TVD) that utilizes a local minmax/maxmi...
The paper presents a novel framework for online tensor inference, addressing the challenges of real-time data processing in applications ...
The paper introduces pplx-embed, a family of multilingual embedding models utilizing diffusion-pretrained language models for enhanced re...
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