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Murali Annavaram

Murali Annavaram has 4 papers in our library, in 2025–2026, most of them on Semitic languages, Reasoning, Bias, fairness & safety; often with Abdulla Alshabanah.

4 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 41 · 243 works · 6,419 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 4 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10228

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. On Using Arabic Language Dialects in Recommendation Systems (2025 · 4 citations)
    This short paper asks whether the dialect a person writes in can help a recommender predict what they will engage with.
  2. Mind the Dialect: NLP Advancements Uncover Fairness Disparities for Arabic Users in Recommendation Systems (2025 · 2 citations)
    The paper asks whether recommendation systems serve Arabic speakers equally, given how strongly regional dialects differ.
  3. DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning (2026 · 1 citation)
    Large reasoning models spend most of their inference time decoding, because every generated token must read the entire, ever-growing KV cache from GPU memory.
  4. EQUIP: EQUivariant preserving In-Place updates for Efficient Token Pruning (2026)
    KV-cache token pruning methods such as StreamingLLM and Heavy Hitters (H2O) keep the cache small, but each eviction leaves gaps.

All works

5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetChaoyang He et al.2022 · 61 citations

 Co-authors here

1 co-author with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 4 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

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