# NLP Related Articles

HTX News Center provides the latest articles and in-depth analysis on "NLP", covering market trends, project updates, tech developments, and regulatory policies in the crypto industry.

Making the Silent Oracle Bones Speak for Three Thousand Years: The First AI-Assisted Interpretation System Mimicking Human Expert Workflow

Breaking the silence of three-thousand-year-old oracle bone inscriptions (OBI) poses immense challenges for researchers, who traditionally rely on laborious cross-referencing across fragmented historical materials. To address this, researchers from Huazhong University of Science and Technology and collaborating institutions have developed AlphaOracle, the first AI system designed to simulate the expert workflow for deciphering OBI. The system integrates a four-step, evidence-based pipeline: 1) parsing and reading-order reconstruction of oracle bone rubbings; 2) morphological analysis of character evolution across historical scripts; 3) contextual verification using large-scale OBI corpora and a specialized masked language model; and 4) literature validation against classical texts and modern scholarly works. AlphaOracle generates comprehensive, traceable reports with candidate interpretations, confidence scores, and source citations for expert review, functioning as an intelligent assistant rather than a final arbiter. In evaluations involving 86 domain experts, 78.7% found the system helpful, estimating an average 64% reduction in analysis time. The system achieved a top-1 accuracy of 23.1% on deciphering withheld known characters and significantly outperformed general-purpose large language models in contextual reasoning tasks. AlphaOracle successfully analyzed several controversial characters, with some results incorporated into authoritative OBI databases. This work demonstrates a promising paradigm where AI enhances the breadth and efficiency of material retrieval and hypothesis generation, while human experts retain the crucial role of deep scholarly judgment, paving the way for systematic AI-assisted research in paleography.

marsbitYesterday 08:41

Making the Silent Oracle Bones Speak for Three Thousand Years: The First AI-Assisted Interpretation System Mimicking Human Expert Workflow

marsbitYesterday 08:41

ACL 2026 Dominated by Chinese Scholars, All Best Paper First Authors Are Chinese, Outstanding Papers Nearly Swept

ACL 2026, held in San Diego, saw a record 12,148 submissions, a 45% increase, with LLM-centric topics dominating. Among 4,462 accepted papers, three were awarded Best Paper, all with Chinese first authors. 1. **"The Imperfective Paradox in Large Language Models"** (Bolei Ma et al.) exposed a "teleological bias" in LLMs: they default to assuming goal-oriented actions succeed, even when context suggests otherwise, acting more as "predictive narrative engines" than logical reasoners. 2. **"Memory efficiency and resource-rational encoding in sentence processing"** (Weijie Xu et al.) showed that constraining Transformer memory with noise injection, mimicking human working memory limits, leads to representations and reading patterns more aligned with human language processing. 3. **"Characterizing the Expressivity of Local Attention in Transformers"** (Jiaoda Li et al.) formally proved, using formal language theory, that local attention strictly increases a Transformer's expressive power, explaining why it often outperforms pure global attention. The conference highlighted the field's scale, with 54% of authors from Mainland China and an average of 6.25 authors per paper. Out of 18 Outstanding Papers awarded, a significant portion also featured prominent contributions from researchers of Chinese descent.

marsbit07/09 11:56

ACL 2026 Dominated by Chinese Scholars, All Best Paper First Authors Are Chinese, Outstanding Papers Nearly Swept

marsbit07/09 11:56

Post-95s Doctoral Graduate Ventures into World Models, FaceMind Raises Tens of Millions of Yuan

The AI startup FaceMind, led by 95-year-old founder Dr. Lu Hongyuan, has secured tens of millions of yuan in a Pre-A Series funding round led by StarLink Capital, with existing investor 360 Capital significantly over-subscribing. Originally focused on on-device multimodal models, the company has pivoted to developing foundational world models, which aim to predict environmental changes for applications like GUI agents and embodied AI (e.g., robotics). Dr. Lu's team gained recognition for research on low-frequency word processing and the "Adam's Law" principle, work later acknowledged by Anthropic. FaceMind's proprietary system emphasizes parameter-efficient, loop-iterative architecture for long-horizon prediction. An early product, "Diedie Club," serves as a testing ground for GUI understanding. Investors highlight the team's research depth, rapid execution, and Dr. Lu's focus on fundamental model architecture over mere scale. The funding will support continued R&D and multi-scenario validation of their world model technology.

marsbit06/26 01:50

Post-95s Doctoral Graduate Ventures into World Models, FaceMind Raises Tens of Millions of Yuan

marsbit06/26 01:50

Hands-on with Hunyuan Hy3 Preview: Tencent's AI, Finally Competitive?

Tencent's Hunyuan AI team has released its latest language model, Hy3 preview, marking a significant step forward for the company's AI capabilities. With 295B total parameters and support for 256K context length, the model employs a mixture-of-experts architecture. It shows improvements in complex logic, instruction following, contextual learning, code generation, and agent task execution. In testing, Hy3 preview demonstrated strong performance in multi-step logical reasoning but showed occasional instability in identifying traps in trick questions. It performed well in extracting key information from disordered meeting transcripts and accurately followed new linguistic rules. As an AI agent, it successfully built functional applications like a Snake game and generated data analysis dashboards, though it sometimes fell short in fully completing complex open-ended tasks. In natural language use, it produced coherent and stylistically appropriate narratives with reduced “AI-like” tone. Priced competitively, Hy3 preview is already integrated into Tencent’s key products, including Tencent Cloud and WorkBuddy. While not leading in every benchmark, it represents a solid, practical model that signals Tencent’s renewed momentum in AI development.

marsbit04/26 07:17

Hands-on with Hunyuan Hy3 Preview: Tencent's AI, Finally Competitive?

marsbit04/26 07:17

From 'Word Unit' to 'Symbol Unit': The Debate Over the Chinese Translation of 'Token' and Its Underlying AI Cognitive Implications

Recent discussions have emerged regarding the official Chinese translation of the AI term "Token," which has been recommended as “词元” (Cíyuán, meaning "word unit") by the National Committee for Terminology in Science and Technology. While this translation is argued to align with historical usage in natural language processing (NLP) and is considered concise and communicable, this article presents a critical counterview advocating for “符元” (Fúyuán, meaning "symbol unit") as a more structurally accurate and future-proof alternative. The author argues that defining Token based on its origin in NLP—as a linguistic semantic unit—overlooks its evolution into a general-purpose, discrete symbolic unit used across multimodal systems (text, image, audio, etc.). Using “词元” ties the concept too narrowly to language, causing cognitive misalignment and semantic drift when applied in non-linguistic contexts. By contrast, “符元” reflects Token’s fundamental role as a symbol in information theory and computation, independent of modality. The article further critiques the reliance on metaphorical extensions (e.g., comparing image patches to “words”) as insufficient for rigorous terminology. It highlights risks including confusion with existing linguistic terms like Lemma (also translated as “词元”), poor cross-lingual reversibility (e.g., difficult back-translation to English), and systemic misunderstanding among non-expert audiences. In conclusion, the author emphasizes that terminology should align with computational essence—not historical usage or explanatory convenience—to ensure conceptual clarity and scalability in AI’s multidisciplinary future. “符元” is proposed as a more neutral, stable, and structurally coherent translation for Token.

marsbit04/10 10:43

From 'Word Unit' to 'Symbol Unit': The Debate Over the Chinese Translation of 'Token' and Its Underlying AI Cognitive Implications

marsbit04/10 10:43

Bybit Launches AI Skills: Powering AI Agents for Crypto Trading With Zero Setup, 253 API Endpoints and Growing

Bybit, the world's second-largest crypto exchange, has launched AI Trading Skill, a feature enabling users to execute trades, access market data, and manage assets using natural language through major AI assistants like ChatGPT and Claude. With zero-installation setup and compatibility across AI platforms, it offers access to 253 API endpoints covering market intelligence, spot and derivatives trading, Earn products, account management, and advanced features like WebSocket streams. The system includes security safeguards such as testnet trading simulations, mandatory user confirmations for live transactions, and secure API authentication. This release represents Bybit's most comprehensive AI integration to date, transforming complex trading operations into simple conversational commands.

TheNewsCrypto03/13 14:18

Bybit Launches AI Skills: Powering AI Agents for Crypto Trading With Zero Setup, 253 API Endpoints and Growing

TheNewsCrypto03/13 14:18

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