Evaluating LLMLingua-2 at 2x compression on LLaDA shows non-uniform transfer to diffusion LLMs, with mathematical reasoning degrading substantially despite high BERTScore while summarization remains more robust.
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Bleu: a method for automatic evaluation of machine translation
11 Pith papers cite this work. Polarity classification is still indexing.
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S2ST-Omni 2 uses typology-informed hierarchical encoding, gated Dual-CTC, and typology-aware prompting to improve multilingual S2ST over flat-label baselines on CVSS-C, with gains in low-data regimes.
EKD trains lightweight NMT students progressively from a chain of teachers with rising capacity, achieving BLEU scores within 0.08 of the largest teacher on IWSLT-14.
RIHA proposes a hierarchical alignment transformer that uses multi-scale visual and textual feature pyramids plus optimal transport to generate more accurate radiology reports from medical images.
LLM-ReSum uses LLM self-evaluation in a closed feedback loop to refine summaries, improving factual accuracy by up to 33% and coverage by 39% with 89% human preference.
CoDe-R refines LLM decompiler output via rationale-guided semantic injection and dynamic fallback inference, making a 1.3B model the first to exceed 50% average re-executability on HumanEval-Decompile.
Chat-Scene++ improves 3D scene understanding in multimodal LLMs by representing scenes as context-rich object sequences with identifier tokens and grounded chain-of-thought reasoning, reaching state-of-the-art on five benchmarks using pre-trained encoders.
RETROFIT enables continual learning for malware detection and binary summarization by retrospective-free parameter merging with low-rank sparse updates and confidence-guided arbitration, improving retention and generalization without historical data.
A dependency-aware prompt pipeline with structured JSON intermediates produces coherent, scalable RPG worlds and quests from LLMs.
CoT prompting improves LLM performance on control-flow deobfuscation of C benchmarks, yielding ~16% better CFG reconstruction and ~20.5% better semantic preservation for GPT5 versus zero-shot prompting.
A globally video-guided multimodal translation framework retrieves semantically related video segments with a vector database and applies attention mechanisms to improve subtitle translation accuracy in long videos.
citing papers explorer
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Prompt Compression in Diffusion Large Language Models: Evaluating LLMLingua-2 on LLaDA
Evaluating LLMLingua-2 at 2x compression on LLaDA shows non-uniform transfer to diffusion LLMs, with mathematical reasoning degrading substantially despite high BERTScore while summarization remains more robust.
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From Flat Language Labels to Typological Priors: Structured Language Conditioning for Multilingual Speech-to-Speech Translation
S2ST-Omni 2 uses typology-informed hierarchical encoding, gated Dual-CTC, and typology-aware prompting to improve multilingual S2ST over flat-label baselines on CVSS-C, with gains in low-data regimes.
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Evolving Knowledge Distillation for Lightweight Neural Machine Translation
EKD trains lightweight NMT students progressively from a chain of teachers with rising capacity, achieving BLEU scores within 0.08 of the largest teacher on IWSLT-14.
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RIHA: Report-Image Hierarchical Alignment for Radiology Report Generation
RIHA proposes a hierarchical alignment transformer that uses multi-scale visual and textual feature pyramids plus optimal transport to generate more accurate radiology reports from medical images.
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LLM-ReSum: A Framework for LLM Reflective Summarization through Self-Evaluation
LLM-ReSum uses LLM self-evaluation in a closed feedback loop to refine summaries, improving factual accuracy by up to 33% and coverage by 39% with 89% human preference.
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CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference
CoDe-R refines LLM decompiler output via rationale-guided semantic injection and dynamic fallback inference, making a 1.3B model the first to exceed 50% average re-executability on HumanEval-Decompile.
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Chat-Scene++: Exploiting Context-Rich Object Identification for 3D LLM
Chat-Scene++ improves 3D scene understanding in multimodal LLMs by representing scenes as context-rich object sequences with identifier tokens and grounded chain-of-thought reasoning, reaching state-of-the-art on five benchmarks using pre-trained encoders.
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Retrofit: Continual Learning with Controlled Forgetting for Binary Security Detection and Analysis
RETROFIT enables continual learning for malware detection and binary summarization by retrospective-free parameter merging with low-rank sparse updates and confidence-guided arbitration, improving retention and generalization without historical data.
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From World-Gen to Quest-Line: A Dependency-Driven Prompt Pipeline for Coherent RPG Generation
A dependency-aware prompt pipeline with structured JSON intermediates produces coherent, scalable RPG worlds and quests from LLMs.
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Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks
CoT prompting improves LLM performance on control-flow deobfuscation of C benchmarks, yielding ~16% better CFG reconstruction and ~20.5% better semantic preservation for GPT5 versus zero-shot prompting.
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Video-guided Machine Translation with Global Video Context
A globally video-guided multimodal translation framework retrieves semantically related video segments with a vector database and applies attention mechanisms to improve subtitle translation accuracy in long videos.