Negar Arabzadeh

Postdoc @UCBerkeley @BerkeleySky |👩🏻‍💻Prev @google, @MSFTResearch, @SpotifyResearch | 📚@UWaterloo | Interested in Information Retrieval

[Negar Arabzadeh @NegarEmpr]

So excited to share that I received the SIGIR Early Career Research Award! 🥹
I still remember attending my first SIGIR, watching someone receive this award, and thinking, “There’s no way that could ever be me.” And now, here I am!😵
This truly means so much to me. Thank you to the @ACMSIGIR community for recognizing my contributions. #SIGIR2026

P.S. Get yourself a PhD supervisor who matches your award-celebration energy 😄 So cool to celebrate this moment together! @claclarke

[Niloofar @niloofar_mire]

@willdepue @OpenAI “The third world makes very little contribution to science” is SUCH A FALSE statement!!! Do u know how many of the top ai researchers in these institutions u are crediting so much come from third world countries and did their undergrads there?? U cant conflate things this much

[Negar Arabzadeh @NegarEmpr]

@sadjadeb is presenting a nice work from Reviewerly on peer review claim verification now in Hall H poster 103 at #EMNLP2026
Come say hi is you are working on topics related to peer review!

[Negar Arabzadeh @NegarEmpr]

Me and drake are in hall H poster 295 at #EMNLP2026

[Negar Arabzadeh @NegarEmpr]

I'll be at #EMNLP2026 in Budapest this week! 🎉 🇭🇺
Presenting "RAG over Thinking Traces Can Improve Reasoning Tasks" today at 11 AM
📍Poster Session A, Hall H.
Come say hi! happy to chat about reasoning, RAG, and everything in between!

[Negar Arabzadeh @NegarEmpr]

1/ Thrilled to introduce T³: a corpus for RAG over reasoning tasks, built from thinking traces.
We show that surprisingly RAG can improve reasoning— with the right corpus.
Rag with Transformed Thinking Traces T³ gain by up to 43.9% on AIME 2025-2026.
🔗 https://t.co/9GPxKnszte 🧵

[Negar Arabzadeh @NegarEmpr]

cc the late-interaction crew: @lateinteraction @bclavie @antoine_chaffin @raphaelsrty @macavaney @ManuelFaysse
Curious to hear what you think!

[Negar Arabzadeh @NegarEmpr]

1/ 💰Multi-vector retrieval shouldn’t charge you by the token!
🎉 Excited to share FLINT (Fixed-budget Late INTeraction), a late-interaction retriever designed for long, complex queries with up to 89% reduction in index and 23-170× faster retrieval latency.⚡

🎛️ FLINT gives a vector-budget knob to balance storage, latency, and quality.

📄 Paper: https://t.co/GO5yum1763

How does it work? 🧵

ColBERT stores and compares one vector per token. FLINT pools every query and every document into a fixed number of vectors, so there’s far less to store and far fewer comparisons at search time.

[Negar Arabzadeh @NegarEmpr]

4/ We evaluated FLINT with different backbones on general retrieval benchmarks like BEIR and more complex retrieval tasks in BrowseComp+, TREC Tip-of-the-Tongue, and CRUMB. we also explored impact of vector budgets of 16, 32, and 64.

📄 Paper: https://t.co/GO5yum1763
💻 Code: https://t.co/Wfw1C08NoV
🤗 Models: https://t.co/OZHKTpk5Em

Huge thanks to @matei_zaharia and especially @HimankHanda for leading this work 🔥

[Haolun Wu @Haolun_Wu0203]

📢 𝗔𝗔𝗔𝗜 𝟮𝟬𝟮𝟳 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝗣𝗮𝗽𝗲𝗿𝘀
𝗧𝗿𝘂𝘀𝘁𝘄𝗼𝗿𝘁𝗵𝘆 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀: 𝘼𝙣 𝘼𝙜𝙚𝙣𝙩 𝙊𝙥𝙚𝙧𝙖𝙩𝙞𝙣𝙜 𝙎𝙮𝙨𝙩𝙚𝙢 𝙋𝙚𝙧𝙨𝙥𝙚𝙘𝙩𝙞𝙫𝙚
📍 𝗣𝗮𝗹𝗮𝗶𝘀 𝗱𝗲𝘀 𝗖𝗼𝗻𝗴𝗿𝗲̀𝘀, 𝗠𝗼𝗻𝘁𝗿𝗲́𝗮𝗹, 𝗖𝗮𝗻𝗮𝗱𝗮 🇨🇦
🗓️ 𝗙𝗲𝗯𝗿𝘂𝗮𝗿𝘆 𝟮𝟮–𝟮𝟯, 𝟮𝟬𝟮𝟳 (one-day workshop, exact day TBA)

AI agents now continuously evolve. How do we keep them trustworthy?

💡 𝗪𝗵𝘆 𝗮 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 𝗽𝗿𝗼𝗯𝗹𝗲𝗺?
Many failures come not from a broken model, but from a bad memory, an over-privileged tool, or an update that cannot be undone. Operating systems 🖥️ solved this long ago. We bring that lens to agents, making their evolution 𝘁𝗿𝗮𝗰𝗲𝗮𝗯𝗹𝗲, 𝗯𝗼𝘂𝗻𝗱𝗲𝗱, 𝗮𝗻𝗱 𝗿𝗲𝘃𝗲𝗿𝘀𝗶𝗯𝗹𝗲 🛡️

📌 𝗧𝗼𝗽𝗶𝗰𝘀
🧠 𝗠𝗲𝗺𝗼𝗿𝘆 (File systems): provenance, isolation, rollback
🛠️ 𝗧𝗼𝗼𝗹𝘀 & 𝗦𝗸𝗶𝗹𝗹𝘀 (Permissions): least privilege, sandboxing, revocation
📈 𝗠𝗼𝗱𝗲𝗹𝘀 & 𝗣𝗼𝗹𝗶𝗰𝗶𝗲𝘀 (System updates): versioning, no silent alignment drift
🤝 𝗠𝘂𝗹𝘁𝗶-𝗔𝗴𝗲𝗻𝘁 (Process isolation): stop one failure from spreading
📊 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 (Logging): trace every failure to the change behind it

🎤 𝗦𝗽𝗲𝗮𝗸𝗲𝗿𝘀 & 𝗣𝗮𝗻𝗲𝗹𝗶𝘀𝘁𝘀: @Yoshua_Bengio (UdeM, LawZero, Mila), @MengdiWang10 (Princeton), @du_yilun (Harvard), @hugo_larochelle (Mila), @ZheqingZhu (Pokee AI), and @yzhao010 (USC).

⏰ 𝗞𝗲𝘆 𝗗𝗮𝘁𝗲𝘀 & 𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻
📝 Submission deadline: Nov 20, 2026 (AoE)
📬 Author notification: Dec 2, 2026 (AoE)
- Full papers: 8 pages; Short / position papers: 4 pages
- Double-blind review, AAAI format

🔗 𝗪𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝗪𝗲𝗯𝘀𝗶𝘁𝗲: https://t.co/UrYfA8Nbe7
📝 𝗣𝗮𝗽𝗲𝗿 𝗦𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻: https://t.co/1gKvvoefDn
📢 𝗜𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗲𝗱 𝗶𝗻 𝗯𝗲𝗰𝗼𝗺𝗶𝗻𝗴 𝗮 𝘄𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝘀𝗽𝗼𝗻𝘀𝗼𝗿? Contact us at [email protected]

Happy to organize with @NegarEmpr, @HuaWenyue31539, @BangL93, and @lcharlin.

Big thanks to the support and advisory from @StevenYuan666, Yankai Chen, Tianyu Shi, @BokwaiHo, @preslav_nakov, Steve Liu, @alex_pentland

We look forward to seeing you in Montréal! 🇨🇦

#AAAI2027 #AIAgents #TrustworthyAI #AISafety #LLM #CallForPapers

[Negar Arabzadeh @NegarEmpr]

Excited to be co-organizing our Trust4RSI-Agent Workshop at #AAAI2027 ! A Workshop on Trustworthy Evolution of AI Agents! 🚀

🥳We have an amazing lineup of speakers and panelists: @Yoshua_Bengio , @MengdiWang10 , @du_yilun , @hugo_larochelle , @ZheqingZhu , and @__yuezhao__ !

📝 Submission deadline: November 20, 2026
📬 Author notification: December 2, 2026
📍 February 22–23, 2027 · Montréal, Canada

🌐 https://t.co/zSASeQheqd

Please share with colleagues working in this space and looking forward to your submissions!

Happy to be organizing this alongside @Haolun_Wu0203 @HuaWenyue31539 @BangL93 @lcharlin! #AAAI2027 #AIAgents

[Negar Arabzadeh @NegarEmpr]

Had a great time presenting DeepScholar-Bench at #COLM2026 today! Lots of interesting conversations and interactions! 🤩

If you’re building a deep research system, give our benchmark a try!

@COLM_conf has been such an engaging and fun conference so far! 🙌

[Negar Arabzadeh @NegarEmpr]

Today at #COLM2026 I will present DeepScholar-Bench and how we can evaluate AI-generated research synthesis!

📍 Imperial Ballroom, Poster #72
🕚 Today, 11 AM–1 PM

Come stop by! Would love to chat!

[Negar Arabzadeh @NegarEmpr]

I'll be BARTing over to #COLM2026 this week 🚇😄

Around all week and happy to chat about search agents & deep research systems!

📄 Thu: DeepScholar-Bench
https://t.co/feowevia1G
📄 Fri: Multi-Agent Transactive Memory @ Lifelong Agents Workshop
https://t.co/zAp40nkicO

[Danny To Eun Kim @TEKnologyy]

Agent Swarms are scaling to 1000+ agents, and your message board gets congested. Who builds search for them? #COLM2026
📍Lifelong Agent workshop (Friday)

[Negar Arabzadeh @NegarEmpr]

I'll be BARTing over to #COLM2026 this week 🚇😄

Around all week and happy to chat about search agents & deep research systems!

📄 Thu: DeepScholar-Bench
https://t.co/feowevia1G
📄 Fri: Multi-Agent Transactive Memory @ Lifelong Agents Workshop
https://t.co/zAp40nkicO

[Shengyao Zhuang @ShengyaoZhuang]

For IR folks: @xueguang_ma and I quickly tested Jev as a pointwise/pairwise/setwise/listwise reranker on the classic DL19 and DL20, reranking the top 100 BM25 results. It is pretty good and cheap.

[Melissa Pan @melissapan]

Quick intro video on 💰HarnessTax💰 is out!!

I also shared some thoughts on what it means for our community to be aware of such cost in coding agents at the end!

[Prasann Singhal @prasann_singhal]

Could long-context architectures “find all contradictions” in a science literature? Not yet! 🧵

We study a new class of "high-complexity” tasks whose difficulty scales quadratically with corpus size (as opposed to linearly), reversing common LCLM decisions! (block-sparse attention, hybrid models…)

[Negar Arabzadeh @NegarEmpr]

@mattjustram Haha thanks matt!

[Negar Arabzadeh @NegarEmpr]

@CShorten30 @amin_bigdelii @radin_hrad @ebrahim_bagheri @claclarke @sadjadeb Thanks @CShorten30 !

[Negar Arabzadeh @NegarEmpr]

1/ We’re excited to share Question’s Gambit module for search agents. ♛

🥇Question Gambit got first on the BrowseComp-Plus leaderboard for recall with BM25 as our only retriever!

📈 It focuses on the first retrieval move in search agents and got 96.6% recall with about 6 times fewer agent search calls.

Same BM25 index. Same agent loop. Just a better opening move.
📄 Paper:
https://t.co/isT50SC1Aa